{"id":3467,"date":"2022-03-02T15:41:02","date_gmt":"2022-03-02T15:41:02","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/?post_type=chapter&#038;p=3467"},"modified":"2022-04-06T17:37:48","modified_gmt":"2022-04-06T17:37:48","slug":"forming-connections-in-1d","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/chapter\/forming-connections-in-1d\/","title":{"raw":"Forming Connections in 1D: Datasets and Statistical Questions","rendered":"Forming Connections in 1D: Datasets and Statistical Questions"},"content":{"raw":"<div class=\"textbox learning-objectives\">\r\n<h3>Objectives for the activity<\/h3>\r\nDuring this activity, you will:\r\n<ul>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Determine whether a question is a good statistical question.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Determine whether a question can be answered with a given set of data.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Construct statistical questions that can be answered with a given set of data.<\/li>\r\n<\/ul>\r\n<\/div>\r\nIn <em>What to Know [1D], <\/em>you learned about the qualities of a good statistical question and how to identify the observational units and variables present in the data used to answer a statistical question. In this activity, you'll make determinations about statistical questions and you'll also see that data must be collected with purpose so that the data are appropriate to answer the question of interest.\r\n<h2>Bad Drivers and Good Questions<\/h2>\r\nIn the article you read in the preview assignment, Mona Chalabi used data to try to answer the question \u201cWhich U.S. state has the worst drivers?\u201d We'll explore the dataset Chalabi used to help us recognize the qualities of a good statistical question and how appropriately chosen data support its investigation.\r\n\r\n<img class=\"wp-image-1065 aligncenter\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/5738\/2022\/01\/11233048\/Picture66-300x200.jpg\" alt=\"A man using his phone while driving\" width=\"384\" height=\"256\" \/>\r\n<div class=\"textbox tryit\">\r\n<h3>Guidance<\/h3>\r\n<span style=\"background-color: #e6daf7;\">[Intro: \"In the\u00a0<em>WTK<\/em> preview, you read a list of\u00a0some of the qualities of a good statistical question. Do you remember what they were? If you haven't yet, list some of these in your notebook now. How did you do? If you need to see the list again, it appears above Question 1 below. Did you remember most of them? If you didn't, that's okay; you have another chance today to record the list. Hopefully though, you do remember the two key qualities of a good statistical question: it won't have an exact answer and it will always anticipate variability. In a moment, you'll use the list of qualities of a good statistical question to answer Question 1 in this activity.\u00a0<\/span>\r\n\r\n<span style=\"background-color: #e6daf7;\">But first, let's turn our attention to the data. What makes a data set appropriate to use to answer a question? What kind of data did Mona Chalabi use to answer the question, \"Which U.S. state has the worst drivers?\" in the article? Write some ideas down in your notebook. If you don't remember, you can review the study again at\u00a0<a href=\"https:\/\/fivethirtyeight.com\/features\/which-state-has-the-worst-drivers\/\">https:\/\/fivethirtyeight.com\/features\/which-state-has-the-worst-drivers\/ .<\/a><\/span>\r\n\r\n<span style=\"background-color: #e6daf7;\">Let's frame our activity today with the following statement. Two important starting points for a statistical study are making sure that you have a good statistical question and making sure the data that you plan to collect are the appropriate data to answer that question.\".]<\/span>\r\n\r\n<\/div>\r\n<h3>Good Questions<\/h3>\r\nA meaningful discussion of a statistical question necessarily includes a discussion of the data used to investigate it. In the questions that follow, we'll do that with the dataset from Mona Chalabi's study by first exploring whether the question exhibits the qualities of a good statistical question. Then, we'll look at the dataset itself while asking how it supported Chalabi's question, and how it might support other good statistical questions as well. Here's the list you read about in the\u00a0<em>WTK\u00a0<\/em>page.\r\n\r\nQualities of a Good Statistical Question\r\n<ul>\r\n \t<li>The question is relevant and interesting.<\/li>\r\n \t<li>The question deals with some natural variation in the world; in other words, the\u00a0question anticipates variability.<\/li>\r\n \t<li>The question asks us to generalize or find a general tendency among many\u00a0individuals.<\/li>\r\n \t<li>The question is one that needs data in order to be answered.<\/li>\r\n \t<li>The question does not have an exact and precise answer that is easy to find;\u00a0there is some analysis that must be done to answer the question, or the question\u00a0may be answered in multiple ways.<\/li>\r\n \t<li>There can be multiple factors that affect the answer to the question.<\/li>\r\n<\/ul>\r\nWork on your own to answer Question 1, using the qualities of a good statistical question.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Question 1<\/h3>\r\nWhat made that question a good statistical question? Do you think she answered the question well? In particular, were the data she used the right data to answer the question?\r\n\r\n[reveal-answer q=\"270604\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"270604\"]Did the question anticipate variability? How did the data account for the differences in populations between the states? Did it address Chalabi's interpretation of \"bad\" drivers? What were the observational units? Did they match the question of interest?[\/hidden-answer]\r\n\r\n<\/div>\r\n<h3>Appropriate Data<\/h3>\r\nNow let's turn to the data table.\u00a0Here are the first 20 rows of the data table for the bad drivers data that were used in the FiveThirtyEight article you read. Remember that the observational units are listed in the rows (state) and the variables in the columns. See the variable descriptions given below the table.\r\n<table style=\"border-collapse: collapse; width: 99.9999%; height: 308px;\" border=\"1\">\r\n<tbody>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\"><\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">state<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">num_drivers<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">perc_speeding<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">perc_alcohol<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">perc_not_distracted<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">perc_no_previous<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">insurance_premiums<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">losses<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">1<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Alabama<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">18.8<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">39<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">30<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">96<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">80<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">784.55<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">145.08<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">2<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Alaska<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">18.1<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">41<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">90<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">1053.48<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">133.93<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">3<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Arizona<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">18.6<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">35<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">28<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">84<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">96<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">899.47<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">110.35<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">4<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Arkansas<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">22.4<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">18<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">26<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">827.34<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">142.39<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">5<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">California<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">12.0<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">35<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">28<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">91<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">89<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">878.41<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">165.63<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">6<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Colorado<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">13.6<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">37<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">28<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">79<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">835.50<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">139.91<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">7<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Connecticut<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">10.8<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">46<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">36<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">82<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">1068.73<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">167.02<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">8<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Delaware<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">16.2<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">38<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">30<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">99<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">1137.87<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">151.48<\/td>\r\n<\/tr>\r\n<tr style=\"height: 28px;\">\r\n<td style=\"width: 11.1111%; height: 28px;\">9<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">District of Columbia<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">5.9<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">34<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">27<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">100<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">100<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">1273.89<\/td>\r\n<td style=\"width: 11.1111%; height: 28px;\">136.05<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">10<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Florida<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">17.9<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">21<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">29<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">92<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">1160.13<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">144.18<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">11<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Georgia<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">15.6<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">19<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">93<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">913.15<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">142.80<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">12<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Hawaii<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">17.5<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">54<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">41<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">82<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">861.18<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">120.92<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">13<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Idaho<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">15.3<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">36<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">29<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">85<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">98<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">641.96<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">82.75<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">14<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Illinois<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">12.8<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">36<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">34<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">96<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">803.11<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">139.15<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">15<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Indiana<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">14.5<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">29<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">720.46<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">108.92<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">16<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Iowa<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">15.7<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">17<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">97<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">649.06<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">114.47<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">17<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Kansas<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">17.8<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">27<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">24<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">77<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">85<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">780.45<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">133.80<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">18<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Kentucky<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">21.4<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">19<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">23<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">78<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">76<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">872.51<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">137.13<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">19<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Louisiana<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">20.5<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">35<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">33<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">73<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">98<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">1281.55<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">194.78<\/td>\r\n<\/tr>\r\n<tr style=\"height: 14px;\">\r\n<td style=\"width: 11.1111%; height: 14px;\">20<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">Maine<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">15.1<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">38<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">30<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">84<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">661.88<\/td>\r\n<td style=\"width: 11.1111%; height: 14px;\">96.57<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nThe following seven variables are included in the dataset. This format for displaying and describing the variables is often referred to as a <em>data dictionary<\/em>. The variable names are presented in italics followed by a brief description.\r\n<p style=\"padding-left: 30px;\"><em>state<\/em>: All 50 states, plus the District of Columbia\r\n<em>num_drivers<\/em>: Number of drivers involved in fatal collisions per billion miles\r\n<em>perc_speeding<\/em>: Percentage of drivers involved in fatal collisions who were speeding\r\n<em>perc_alcohol<\/em>: Percentage of drivers involved in fatal collisions who were alcohol-impaired\r\n<em>perc_not_distracted<\/em>: Percentage of drivers involved in fatal collisions who were not distracted\r\n<em>perc_no_previous<\/em>: Percentage of drivers involved in fatal collisions who had not been involved in any previous accidents\r\n<em>insurance_premiums<\/em>: Average combined car insurance premiums ($)\r\nlosses: Losses incurred by insurance companies for collisions per insured driver ($)<\/p>\r\nWork individually to answer Question 2 by writing a different statistical question that could be answered by this data.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Question 2<\/h3>\r\nGive an example of another statistical question you could answer given the data that were used in the \u201cWorst Drivers\u201d article.\r\n\r\nNote: Your answer may involve some or all of the variables listed, and you can also consider questions that try to determine whether the variables are related to one another.\r\n\r\n[reveal-answer q=\"382363\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"382363\"]What do you think? Other than, \"Which state has the worst drivers?\" are there other regional breakdowns that could be examined? Do any other variables sound interesting to consider together? [\/hidden-answer]\r\n\r\n<\/div>\r\nOnce you have written your question, come together with others in pairs or small groups to discuss your questions. Answer Question 3 parts A and B about your own question, but use the points as a guide for your discussion.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Question 3<\/h3>\r\nWith your group or partner, discuss your sample questions. Consider the class discussion on good questions and appropriate data. Make sure to answer the following about your own question.\r\n\r\n&nbsp;\r\n\r\nPart A: Is your question a good statistical question? Why or why not?\r\n\r\n&nbsp;\r\n\r\nPart B: Are the bad driver data the appropriate data to use to answer your question? Why or why not?\r\n\r\n[reveal-answer q=\"857068\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"857068\"]Refer to the two key qualities of good statistical questions.[\/hidden-answer]\r\n\r\n<\/div>\r\nNow, choose one of the questions in your group that you wouldn't mind sharing with the class. Go into detail about why you chose the question to answer Question 4. If your group chose a question other than yours, include the answers to Question 3 parts A and B for the new question in your answer to Question 4 as well.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Question 4<\/h3>\r\nWith your group or partner, choose one of your questions to share out with the class. Write the question you chose below, and explain why you chose it. If the question is not your question, make sure to explain what makes the question a good statistical question and why the bad driver data are appropriate to answer it.\r\n\r\n<\/div>\r\n<div class=\"textbox tryit\">\r\n<h3>Guidance<\/h3>\r\n<span style=\"background-color: #e6daf7;\">[Wrap-Up: \"I hope that you had an opportunity to critique questions your classmates had written during this activity. It's challenging to work together to select only one question from your group, especially when there are more than one good question to chose from! You certainly had good practice at collaborative learning in this activity. You'll be ready for the activity in the following section, in which you'll receive some tools for forming effective study groups outside of class. For now, though, let's turn back to today's experience. Take a look back at the objectives at the start of this page to see if you can recognize where each of them appeared in the activity. You should recognize now that\u00a0analyzing statistics is an investigative\u00a0process that begins with a good question, followed by identification\u00a0of what data are needed to answer that question, followed by the\u00a0actual collection of the data. And data collection is where\u00a0we\u2019re headed soon!\u00a0Before closing this activity, take a few minutes to reflect about writing good statistical questions by answering Question 5.\"\u00a0]<\/span>\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Question 5<\/h3>\r\nAfter hearing the questions shared by the other groups in the class, summarize what you learned about writing good statistical questions and making sure the data available are appropriate to answer those questions.\r\n\r\n[reveal-answer q=\"326722\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"326722\"]Use this space to summarize your own understanding.[\/hidden-answer]\r\n\r\n<\/div>\r\n&nbsp;","rendered":"<div class=\"textbox learning-objectives\">\n<h3>Objectives for the activity<\/h3>\n<p>During this activity, you will:<\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Determine whether a question is a good statistical question.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Determine whether a question can be answered with a given set of data.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Construct statistical questions that can be answered with a given set of data.<\/li>\n<\/ul>\n<\/div>\n<p>In <em>What to Know [1D], <\/em>you learned about the qualities of a good statistical question and how to identify the observational units and variables present in the data used to answer a statistical question. In this activity, you&#8217;ll make determinations about statistical questions and you&#8217;ll also see that data must be collected with purpose so that the data are appropriate to answer the question of interest.<\/p>\n<h2>Bad Drivers and Good Questions<\/h2>\n<p>In the article you read in the preview assignment, Mona Chalabi used data to try to answer the question \u201cWhich U.S. state has the worst drivers?\u201d We&#8217;ll explore the dataset Chalabi used to help us recognize the qualities of a good statistical question and how appropriately chosen data support its investigation.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-1065 aligncenter\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/5738\/2022\/01\/11233048\/Picture66-300x200.jpg\" alt=\"A man using his phone while driving\" width=\"384\" height=\"256\" \/><\/p>\n<div class=\"textbox tryit\">\n<h3>Guidance<\/h3>\n<p><span style=\"background-color: #e6daf7;\">[Intro: &#8220;In the\u00a0<em>WTK<\/em> preview, you read a list of\u00a0some of the qualities of a good statistical question. Do you remember what they were? If you haven&#8217;t yet, list some of these in your notebook now. How did you do? If you need to see the list again, it appears above Question 1 below. Did you remember most of them? If you didn&#8217;t, that&#8217;s okay; you have another chance today to record the list. Hopefully though, you do remember the two key qualities of a good statistical question: it won&#8217;t have an exact answer and it will always anticipate variability. In a moment, you&#8217;ll use the list of qualities of a good statistical question to answer Question 1 in this activity.\u00a0<\/span><\/p>\n<p><span style=\"background-color: #e6daf7;\">But first, let&#8217;s turn our attention to the data. What makes a data set appropriate to use to answer a question? What kind of data did Mona Chalabi use to answer the question, &#8220;Which U.S. state has the worst drivers?&#8221; in the article? Write some ideas down in your notebook. If you don&#8217;t remember, you can review the study again at\u00a0<a href=\"https:\/\/fivethirtyeight.com\/features\/which-state-has-the-worst-drivers\/\">https:\/\/fivethirtyeight.com\/features\/which-state-has-the-worst-drivers\/ .<\/a><\/span><\/p>\n<p><span style=\"background-color: #e6daf7;\">Let&#8217;s frame our activity today with the following statement. Two important starting points for a statistical study are making sure that you have a good statistical question and making sure the data that you plan to collect are the appropriate data to answer that question.&#8221;.]<\/span><\/p>\n<\/div>\n<h3>Good Questions<\/h3>\n<p>A meaningful discussion of a statistical question necessarily includes a discussion of the data used to investigate it. In the questions that follow, we&#8217;ll do that with the dataset from Mona Chalabi&#8217;s study by first exploring whether the question exhibits the qualities of a good statistical question. Then, we&#8217;ll look at the dataset itself while asking how it supported Chalabi&#8217;s question, and how it might support other good statistical questions as well. Here&#8217;s the list you read about in the\u00a0<em>WTK\u00a0<\/em>page.<\/p>\n<p>Qualities of a Good Statistical Question<\/p>\n<ul>\n<li>The question is relevant and interesting.<\/li>\n<li>The question deals with some natural variation in the world; in other words, the\u00a0question anticipates variability.<\/li>\n<li>The question asks us to generalize or find a general tendency among many\u00a0individuals.<\/li>\n<li>The question is one that needs data in order to be answered.<\/li>\n<li>The question does not have an exact and precise answer that is easy to find;\u00a0there is some analysis that must be done to answer the question, or the question\u00a0may be answered in multiple ways.<\/li>\n<li>There can be multiple factors that affect the answer to the question.<\/li>\n<\/ul>\n<p>Work on your own to answer Question 1, using the qualities of a good statistical question.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>Question 1<\/h3>\n<p>What made that question a good statistical question? Do you think she answered the question well? In particular, were the data she used the right data to answer the question?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q270604\">Hint<\/span><\/p>\n<div id=\"q270604\" class=\"hidden-answer\" style=\"display: none\">Did the question anticipate variability? How did the data account for the differences in populations between the states? Did it address Chalabi&#8217;s interpretation of &#8220;bad&#8221; drivers? What were the observational units? Did they match the question of interest?<\/div>\n<\/div>\n<\/div>\n<h3>Appropriate Data<\/h3>\n<p>Now let&#8217;s turn to the data table.\u00a0Here are the first 20 rows of the data table for the bad drivers data that were used in the FiveThirtyEight article you read. Remember that the observational units are listed in the rows (state) and the variables in the columns. See the variable descriptions given below the table.<\/p>\n<table style=\"border-collapse: collapse; width: 99.9999%; height: 308px;\">\n<tbody>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\"><\/td>\n<td style=\"width: 11.1111%; height: 14px;\">state<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">num_drivers<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">perc_speeding<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">perc_alcohol<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">perc_not_distracted<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">perc_no_previous<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">insurance_premiums<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">losses<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">1<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Alabama<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">18.8<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">39<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">30<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">96<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">80<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">784.55<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">145.08<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">2<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Alaska<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">18.1<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">41<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">90<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">1053.48<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">133.93<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">3<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Arizona<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">18.6<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">35<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">28<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">84<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">96<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">899.47<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">110.35<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">4<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Arkansas<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">22.4<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">18<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">26<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">827.34<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">142.39<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">5<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">California<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">12.0<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">35<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">28<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">91<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">89<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">878.41<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">165.63<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">6<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Colorado<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">13.6<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">37<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">28<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">79<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">835.50<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">139.91<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">7<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Connecticut<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">10.8<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">46<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">36<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">82<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">1068.73<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">167.02<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">8<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Delaware<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">16.2<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">38<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">30<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">99<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">1137.87<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">151.48<\/td>\n<\/tr>\n<tr style=\"height: 28px;\">\n<td style=\"width: 11.1111%; height: 28px;\">9<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">District of Columbia<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">5.9<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">34<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">27<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">100<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">100<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">1273.89<\/td>\n<td style=\"width: 11.1111%; height: 28px;\">136.05<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">10<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Florida<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">17.9<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">21<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">29<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">92<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">1160.13<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">144.18<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">11<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Georgia<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">15.6<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">19<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">93<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">913.15<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">142.80<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">12<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Hawaii<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">17.5<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">54<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">41<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">82<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">861.18<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">120.92<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">13<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Idaho<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">15.3<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">36<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">29<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">85<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">98<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">641.96<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">82.75<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">14<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Illinois<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">12.8<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">36<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">34<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">94<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">96<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">803.11<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">139.15<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">15<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Indiana<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">14.5<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">29<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">95<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">720.46<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">108.92<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">16<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Iowa<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">15.7<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">17<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">25<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">97<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">649.06<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">114.47<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">17<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Kansas<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">17.8<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">27<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">24<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">77<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">85<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">780.45<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">133.80<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">18<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Kentucky<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">21.4<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">19<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">23<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">78<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">76<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">872.51<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">137.13<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">19<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Louisiana<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">20.5<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">35<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">33<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">73<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">98<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">1281.55<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">194.78<\/td>\n<\/tr>\n<tr style=\"height: 14px;\">\n<td style=\"width: 11.1111%; height: 14px;\">20<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">Maine<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">15.1<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">38<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">30<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">87<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">84<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">661.88<\/td>\n<td style=\"width: 11.1111%; height: 14px;\">96.57<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>The following seven variables are included in the dataset. This format for displaying and describing the variables is often referred to as a <em>data dictionary<\/em>. The variable names are presented in italics followed by a brief description.<\/p>\n<p style=\"padding-left: 30px;\"><em>state<\/em>: All 50 states, plus the District of Columbia<br \/>\n<em>num_drivers<\/em>: Number of drivers involved in fatal collisions per billion miles<br \/>\n<em>perc_speeding<\/em>: Percentage of drivers involved in fatal collisions who were speeding<br \/>\n<em>perc_alcohol<\/em>: Percentage of drivers involved in fatal collisions who were alcohol-impaired<br \/>\n<em>perc_not_distracted<\/em>: Percentage of drivers involved in fatal collisions who were not distracted<br \/>\n<em>perc_no_previous<\/em>: Percentage of drivers involved in fatal collisions who had not been involved in any previous accidents<br \/>\n<em>insurance_premiums<\/em>: Average combined car insurance premiums ($)<br \/>\nlosses: Losses incurred by insurance companies for collisions per insured driver ($)<\/p>\n<p>Work individually to answer Question 2 by writing a different statistical question that could be answered by this data.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>Question 2<\/h3>\n<p>Give an example of another statistical question you could answer given the data that were used in the \u201cWorst Drivers\u201d article.<\/p>\n<p>Note: Your answer may involve some or all of the variables listed, and you can also consider questions that try to determine whether the variables are related to one another.<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q382363\">Hint<\/span><\/p>\n<div id=\"q382363\" class=\"hidden-answer\" style=\"display: none\">What do you think? Other than, &#8220;Which state has the worst drivers?&#8221; are there other regional breakdowns that could be examined? Do any other variables sound interesting to consider together? <\/div>\n<\/div>\n<\/div>\n<p>Once you have written your question, come together with others in pairs or small groups to discuss your questions. Answer Question 3 parts A and B about your own question, but use the points as a guide for your discussion.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>Question 3<\/h3>\n<p>With your group or partner, discuss your sample questions. Consider the class discussion on good questions and appropriate data. Make sure to answer the following about your own question.<\/p>\n<p>&nbsp;<\/p>\n<p>Part A: Is your question a good statistical question? Why or why not?<\/p>\n<p>&nbsp;<\/p>\n<p>Part B: Are the bad driver data the appropriate data to use to answer your question? Why or why not?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q857068\">Hint<\/span><\/p>\n<div id=\"q857068\" class=\"hidden-answer\" style=\"display: none\">Refer to the two key qualities of good statistical questions.<\/div>\n<\/div>\n<\/div>\n<p>Now, choose one of the questions in your group that you wouldn&#8217;t mind sharing with the class. Go into detail about why you chose the question to answer Question 4. If your group chose a question other than yours, include the answers to Question 3 parts A and B for the new question in your answer to Question 4 as well.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>Question 4<\/h3>\n<p>With your group or partner, choose one of your questions to share out with the class. Write the question you chose below, and explain why you chose it. If the question is not your question, make sure to explain what makes the question a good statistical question and why the bad driver data are appropriate to answer it.<\/p>\n<\/div>\n<div class=\"textbox tryit\">\n<h3>Guidance<\/h3>\n<p><span style=\"background-color: #e6daf7;\">[Wrap-Up: &#8220;I hope that you had an opportunity to critique questions your classmates had written during this activity. It&#8217;s challenging to work together to select only one question from your group, especially when there are more than one good question to chose from! You certainly had good practice at collaborative learning in this activity. You&#8217;ll be ready for the activity in the following section, in which you&#8217;ll receive some tools for forming effective study groups outside of class. For now, though, let&#8217;s turn back to today&#8217;s experience. Take a look back at the objectives at the start of this page to see if you can recognize where each of them appeared in the activity. You should recognize now that\u00a0analyzing statistics is an investigative\u00a0process that begins with a good question, followed by identification\u00a0of what data are needed to answer that question, followed by the\u00a0actual collection of the data. And data collection is where\u00a0we\u2019re headed soon!\u00a0Before closing this activity, take a few minutes to reflect about writing good statistical questions by answering Question 5.&#8221;\u00a0]<\/span><\/p>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>Question 5<\/h3>\n<p>After hearing the questions shared by the other groups in the class, summarize what you learned about writing good statistical questions and making sure the data available are appropriate to answer those questions.<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q326722\">Hint<\/span><\/p>\n<div id=\"q326722\" class=\"hidden-answer\" style=\"display: none\">Use this space to summarize your own understanding.<\/div>\n<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n","protected":false},"author":493460,"menu_order":23,"template":"","meta":{"_candela_citation":"[]","CANDELA_OUTCOMES_GUID":"","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-3467","chapter","type-chapter","status-publish","hentry"],"part":3418,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/3467","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/users\/493460"}],"version-history":[{"count":12,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/3467\/revisions"}],"predecessor-version":[{"id":4259,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/3467\/revisions\/4259"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/parts\/3418"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/3467\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/media?parent=3467"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapter-type?post=3467"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/contributor?post=3467"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/license?post=3467"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}