{"id":1640,"date":"2018-01-15T16:49:05","date_gmt":"2018-01-15T16:49:05","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/introstats1\/chapter\/course-contents-at-a-glance\/"},"modified":"2018-01-16T21:54:21","modified_gmt":"2018-01-16T21:54:21","slug":"course-contents-at-a-glance","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/suny-suffolk-introstats1\/chapter\/course-contents-at-a-glance\/","title":{"raw":"Course Contents at a Glance","rendered":"Course Contents at a Glance"},"content":{"raw":"<img class=\"aligncenter wp-image-220\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/132\/2018\/01\/15164903\/binoculars2.png\" alt=\"an icon of a pair of binoculars\" width=\"250\" height=\"142\" \/>\r\n\r\nThe following list shows a summary of the topics covered in this course. To see all of the course pages, visit the\u00a0<a href=\"https:\/\/courses.lumenlearning.com\/introstats1\/\" target=\"_blank\" rel=\"noopener\">Table of Contents<\/a>.\r\n<h2>Module 1: Sampling and Data<\/h2>\r\n<ul>\r\n \t<li>Definitions of Statistics, Probability, and Key Terms<\/li>\r\n \t<li>Sampling and Data<\/li>\r\n \t<li>Frequency, Frequency Tables, and Levels of Measurement<\/li>\r\n \t<li>Experimental Design and Ethics<\/li>\r\n<\/ul>\r\n<h2>Module 2: Descriptive Statistics<\/h2>\r\n<ul>\r\n \t<li class=\"chapter standard\">Stem-and-Leaf Graphs (Stemplots)<\/li>\r\n \t<li>Measures of the Location of the Data<\/li>\r\n \t<li>Histograms, Frequency Polygons, and Time Series Graphs<\/li>\r\n \t<li>Box Plots<\/li>\r\n \t<li>Measures of the Center of the Data<\/li>\r\n \t<li>Skewness and the Mean, Median, and Mode<\/li>\r\n \t<li>Measures of the Spread of Data<\/li>\r\n \t<li>When to use each measure of Central Tendency<\/li>\r\n<\/ul>\r\n<h2><strong>Module 3: Probability<\/strong><\/h2>\r\n<ul>\r\n \t<li>The Terminology of Probability<\/li>\r\n \t<li>Independent and Mutually Exclusive Events<\/li>\r\n \t<li>Two Basic Rules of Probability<\/li>\r\n \t<li>Contingency Tables<\/li>\r\n \t<li>Tree and Venn Diagrams<\/li>\r\n<\/ul>\r\n<h2><strong>Module 4: Discrete Random Variables<\/strong><\/h2>\r\n<ul>\r\n \t<li>Probability Distribution Function (PDF) for a Discrete Random Variable<\/li>\r\n \t<li>Mean or Expected Value and Standard Deviation<\/li>\r\n \t<li>Binomial Distribution<\/li>\r\n \t<li>Geometric Distribution<\/li>\r\n \t<li>Poisson Distribution<\/li>\r\n<\/ul>\r\n<h2><strong>Module 5: Continuous Random Variables<\/strong><\/h2>\r\n<ul>\r\n \t<li>Continuous Probability Functions<\/li>\r\n \t<li>The Uniform Distribution<\/li>\r\n \t<li>The Exponential Distribution<\/li>\r\n<\/ul>\r\n<h2><strong>Module 6: Normal Distribution<\/strong><\/h2>\r\n<ul>\r\n \t<li>The Standard Normal Distribution<\/li>\r\n \t<li>Using the Normal Distribution<\/li>\r\n<\/ul>\r\n<h2><strong>Module 7: The Central Limit Theorem<\/strong><\/h2>\r\n<ul>\r\n \t<li>The Central Limit Theorem for Sample Means (Averages)<\/li>\r\n \t<li>The Central Limit Theorem for Sums<\/li>\r\n \t<li>Using the Central Limit Theorem<\/li>\r\n<\/ul>\r\n<h2><strong>Module 8: Confidence Intervals<\/strong><\/h2>\r\n<ul>\r\n \t<li>A Single Population Mean using the Normal Distribution<\/li>\r\n \t<li>A Single Population Mean using the Student Distribution<\/li>\r\n \t<li>A Population Proportion<\/li>\r\n<\/ul>\r\n<h2><strong>Module 9: Hypothesis Testing With One Sample<\/strong><\/h2>\r\n<ul>\r\n \t<li>Null and Alternative Hypotheses<\/li>\r\n \t<li>Outcomes and the Type I and Type II Errors<\/li>\r\n \t<li>Distributions Needed for Hypothesis Testing<\/li>\r\n \t<li>Rare Events, the Sample, Decision and Conclusion<\/li>\r\n \t<li>Additional Informational and Full Hypothesis Test Examples<\/li>\r\n<\/ul>\r\n<h2><strong>Module 10: Hypothesis Testing With Two Samples<\/strong><\/h2>\r\n<ul>\r\n \t<li>Two Population Means with Unknown Standard Deviations<\/li>\r\n \t<li>Two Population Means with Known Standard Deviations<\/li>\r\n \t<li>Comparing Two Independent Population Proportions<\/li>\r\n \t<li>Matched or Paired Samples<\/li>\r\n<\/ul>\r\n<h2><strong>Module 11: The Chi Square Distribution<\/strong><\/h2>\r\n<ul>\r\n \t<li>Facts About the Chi-Square Distribution<\/li>\r\n \t<li>Goodness-of-Fit Test<\/li>\r\n \t<li>Test of Independence<\/li>\r\n \t<li>Test for Homogeneity<\/li>\r\n \t<li>Comparison of the Chi-Square Tests<\/li>\r\n \t<li>Test of a Single Variance<\/li>\r\n<\/ul>\r\n<h2><strong>Module 12: Linear Regression and Correlation<\/strong><\/h2>\r\n<ul>\r\n \t<li>Linear Equations<\/li>\r\n \t<li>Scatter Plots<\/li>\r\n \t<li>The Regression Equation<\/li>\r\n \t<li>Testing the Significance of the Correlation Coefficient<\/li>\r\n \t<li>Prediction<\/li>\r\n \t<li>Outliers<\/li>\r\n<\/ul>\r\n<h2><strong>Module 13: F-Distribution and the One-Way ANOVA<\/strong><\/h2>\r\n<ul>\r\n \t<li>One-Way ANOVA<\/li>\r\n \t<li>The F Distribution and the F-Ratio<\/li>\r\n \t<li>Facts about the F Distribution<\/li>\r\n \t<li>Test of Two Variances<\/li>\r\n \t<li>Relationships in an ANOVA Table<\/li>\r\n<\/ul>\r\n<h2><strong>Module 14: Multiple and Logistic Regression<\/strong><\/h2>\r\n<ul>\r\n \t<li>Model Selection<\/li>\r\n \t<li>Checking Model Assumptions Using Graphs<\/li>\r\n \t<li>Line Fitting, Residuals, and Correlation<\/li>\r\n \t<li>Fitting a Line by Least Linear Regression<\/li>\r\n \t<li class=\"chapter standard\">Types of Outliers in Linear Regression<\/li>\r\n \t<li>Inference for Linear Regression<\/li>\r\n<\/ul>","rendered":"<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-220\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/132\/2018\/01\/15164903\/binoculars2.png\" alt=\"an icon of a pair of binoculars\" width=\"250\" height=\"142\" \/><\/p>\n<p>The following list shows a summary of the topics covered in this course. To see all of the course pages, visit the\u00a0<a href=\"https:\/\/courses.lumenlearning.com\/introstats1\/\" target=\"_blank\" rel=\"noopener\">Table of Contents<\/a>.<\/p>\n<h2>Module 1: Sampling and Data<\/h2>\n<ul>\n<li>Definitions of Statistics, Probability, and Key Terms<\/li>\n<li>Sampling and Data<\/li>\n<li>Frequency, Frequency Tables, and Levels of Measurement<\/li>\n<li>Experimental Design and Ethics<\/li>\n<\/ul>\n<h2>Module 2: Descriptive Statistics<\/h2>\n<ul>\n<li class=\"chapter standard\">Stem-and-Leaf Graphs (Stemplots)<\/li>\n<li>Measures of the Location of the Data<\/li>\n<li>Histograms, Frequency Polygons, and Time Series Graphs<\/li>\n<li>Box Plots<\/li>\n<li>Measures of the Center of the Data<\/li>\n<li>Skewness and the Mean, Median, and Mode<\/li>\n<li>Measures of the Spread of Data<\/li>\n<li>When to use each measure of Central Tendency<\/li>\n<\/ul>\n<h2><strong>Module 3: Probability<\/strong><\/h2>\n<ul>\n<li>The Terminology of Probability<\/li>\n<li>Independent and Mutually Exclusive Events<\/li>\n<li>Two Basic Rules of Probability<\/li>\n<li>Contingency Tables<\/li>\n<li>Tree and Venn Diagrams<\/li>\n<\/ul>\n<h2><strong>Module 4: Discrete Random Variables<\/strong><\/h2>\n<ul>\n<li>Probability Distribution Function (PDF) for a Discrete Random Variable<\/li>\n<li>Mean or Expected Value and Standard Deviation<\/li>\n<li>Binomial Distribution<\/li>\n<li>Geometric Distribution<\/li>\n<li>Poisson Distribution<\/li>\n<\/ul>\n<h2><strong>Module 5: Continuous Random Variables<\/strong><\/h2>\n<ul>\n<li>Continuous Probability Functions<\/li>\n<li>The Uniform Distribution<\/li>\n<li>The Exponential Distribution<\/li>\n<\/ul>\n<h2><strong>Module 6: Normal Distribution<\/strong><\/h2>\n<ul>\n<li>The Standard Normal Distribution<\/li>\n<li>Using the Normal Distribution<\/li>\n<\/ul>\n<h2><strong>Module 7: The Central Limit Theorem<\/strong><\/h2>\n<ul>\n<li>The Central Limit Theorem for Sample Means (Averages)<\/li>\n<li>The Central Limit Theorem for Sums<\/li>\n<li>Using the Central Limit Theorem<\/li>\n<\/ul>\n<h2><strong>Module 8: Confidence Intervals<\/strong><\/h2>\n<ul>\n<li>A Single Population Mean using the Normal Distribution<\/li>\n<li>A Single Population Mean using the Student Distribution<\/li>\n<li>A Population Proportion<\/li>\n<\/ul>\n<h2><strong>Module 9: Hypothesis Testing With One Sample<\/strong><\/h2>\n<ul>\n<li>Null and Alternative Hypotheses<\/li>\n<li>Outcomes and the Type I and Type II Errors<\/li>\n<li>Distributions Needed for Hypothesis Testing<\/li>\n<li>Rare Events, the Sample, Decision and Conclusion<\/li>\n<li>Additional Informational and Full Hypothesis Test Examples<\/li>\n<\/ul>\n<h2><strong>Module 10: Hypothesis Testing With Two Samples<\/strong><\/h2>\n<ul>\n<li>Two Population Means with Unknown Standard Deviations<\/li>\n<li>Two Population Means with Known Standard Deviations<\/li>\n<li>Comparing Two Independent Population Proportions<\/li>\n<li>Matched or Paired Samples<\/li>\n<\/ul>\n<h2><strong>Module 11: The Chi Square Distribution<\/strong><\/h2>\n<ul>\n<li>Facts About the Chi-Square Distribution<\/li>\n<li>Goodness-of-Fit Test<\/li>\n<li>Test of Independence<\/li>\n<li>Test for Homogeneity<\/li>\n<li>Comparison of the Chi-Square Tests<\/li>\n<li>Test of a Single Variance<\/li>\n<\/ul>\n<h2><strong>Module 12: Linear Regression and Correlation<\/strong><\/h2>\n<ul>\n<li>Linear Equations<\/li>\n<li>Scatter Plots<\/li>\n<li>The Regression Equation<\/li>\n<li>Testing the Significance of the Correlation Coefficient<\/li>\n<li>Prediction<\/li>\n<li>Outliers<\/li>\n<\/ul>\n<h2><strong>Module 13: F-Distribution and the One-Way ANOVA<\/strong><\/h2>\n<ul>\n<li>One-Way ANOVA<\/li>\n<li>The F Distribution and the F-Ratio<\/li>\n<li>Facts about the F Distribution<\/li>\n<li>Test of Two Variances<\/li>\n<li>Relationships in an ANOVA Table<\/li>\n<\/ul>\n<h2><strong>Module 14: Multiple and Logistic Regression<\/strong><\/h2>\n<ul>\n<li>Model Selection<\/li>\n<li>Checking Model Assumptions Using Graphs<\/li>\n<li>Line Fitting, Residuals, and Correlation<\/li>\n<li>Fitting a Line by Least Linear Regression<\/li>\n<li class=\"chapter standard\">Types of Outliers in Linear Regression<\/li>\n<li>Inference for Linear Regression<\/li>\n<\/ul>\n\n\t\t\t <section class=\"citations-section\" role=\"contentinfo\">\n\t\t\t <h3>Candela Citations<\/h3>\n\t\t\t\t\t <div>\n\t\t\t\t\t\t <div id=\"citation-list-1640\">\n\t\t\t\t\t\t\t <div class=\"licensing\"><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Original<\/div><ul class=\"citation-list\"><li>Course Contents at a Glance. <strong>Provided by<\/strong>: Lumen Learning. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><\/ul><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Shared previously<\/div><ul class=\"citation-list\"><li>Binoculars Icon. <strong>Authored by<\/strong>: Musmellow. <strong>Provided by<\/strong>: Noun Project. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"https:\/\/thenounproject.com\/term\/binoculars\/1234056\/\">https:\/\/thenounproject.com\/term\/binoculars\/1234056\/<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><\/ul><\/div>\n\t\t\t\t\t\t <\/div>\n\t\t\t\t\t <\/div>\n\t\t\t <\/section>","protected":false},"author":17533,"menu_order":2,"template":"","meta":{"_candela_citation":"[{\"type\":\"cc\",\"description\":\"Binoculars Icon\",\"author\":\"Musmellow\",\"organization\":\"Noun Project\",\"url\":\"https:\/\/thenounproject.com\/term\/binoculars\/1234056\/\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"\"},{\"type\":\"original\",\"description\":\"Course Contents at a Glance\",\"author\":\"\",\"organization\":\"Lumen 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