{"id":23,"date":"2022-06-13T19:50:47","date_gmt":"2022-06-13T19:50:47","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/chapter\/learning-outcomes\/"},"modified":"2022-06-13T19:50:47","modified_gmt":"2022-06-13T19:50:47","slug":"learning-outcomes","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/chapter\/learning-outcomes\/","title":{"raw":"Learning Outcomes","rendered":"Learning Outcomes"},"content":{"raw":"\n<img class=\"aligncenter wp-image-254\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/2025\/2017\/07\/01225024\/outcomes.jpg\" alt=\"icon of a magnifying glass over a list\" width=\"200\" height=\"201\">\n\nThe textbook&nbsp;content and assessments for Introduction to Statistics are aligned to the following learning outcomes.\n<h2>Module 1: Sampling and Data<\/h2>\n<ul>\n \t<li>Recognize and differentiate between key terms.<\/li>\n \t<li>Apply various types of sampling methods to data collection.<\/li>\n \t<li>Create and interpret frequency tables.<\/li>\n<\/ul>\n<h2>Module 2: Descriptive Statistics<\/h2>\n<ul>\n \t<li>Display data graphically and interpret graphs: stemplots, histograms, and box plots.<\/li>\n \t<li>Recognize, describe, and calculate the measures of location of data: quartiles and percentiles.<\/li>\n \t<li>Recognize, describe, and calculate the measures of the center of data: mean, median, and mode.<\/li>\n \t<li>Recognize, describe, and calculate the measures of the spread of data: variance, standard deviation, and range.<\/li>\n<\/ul>\n<h2><strong>Module 3: Probability<\/strong><\/h2>\n<ul>\n \t<li>Understand and use the terminology of probability.<\/li>\n \t<li>Determine whether two events are mutually exclusive and whether two events are independent.<\/li>\n \t<li>Calculate probabilities using the Addition Rules and Multiplication Rules.<\/li>\n \t<li>Construct and interpret Contingency Tables.<\/li>\n \t<li>Construct and interpret Venn Diagrams.<\/li>\n \t<li>Construct and interpret Tree Diagrams.<\/li>\n<\/ul>\n<h2><strong>Module 4: Discrete Random Variables<\/strong><\/h2>\n<ul>\n \t<li>Recognize and understand discrete probability distribution functions, in general.<\/li>\n \t<li>Calculate and interpret expected values.<\/li>\n \t<li>Recognize the binomial probability distribution and apply it appropriately.<\/li>\n \t<li>Recognize the Poisson probability distribution and apply it appropriately.<\/li>\n \t<li>Recognize the geometric probability distribution and apply it appropriately.<\/li>\n \t<li>Recognize the hypergeometric probability distribution and apply it appropriately.<\/li>\n \t<li>Classify discrete word problems by their distributions.<\/li>\n<\/ul>\n<h2><strong>Module 5: Continuous Random Variables<\/strong><\/h2>\n<ul>\n \t<li>Recognize and understand continuous probability density functions in general.<\/li>\n \t<li>Recognize the uniform probability distribution and apply it appropriately.<\/li>\n \t<li>Recognize the exponential probability distribution and apply it appropriately.<\/li>\n<\/ul>\n<h2><strong>Module 6: Normal Distribution<\/strong><\/h2>\n<ul>\n \t<li>Recognize the normal probability distribution and apply it appropriately.<\/li>\n \t<li>Recognize the standard normal probability distribution and apply it appropriately.<\/li>\n \t<li>Compare normal probabilities by converting to the standard normal distribution.<\/li>\n<\/ul>\n<h2><strong>Module 7: The Central Limit Theorem<\/strong><\/h2>\n<ul>\n \t<li>Recognize central limit theorem problems.<\/li>\n \t<li>Classify continuous word problems by their distributions.<\/li>\n \t<li>Apply and interpret the central limit theorem for means.<\/li>\n \t<li>Apply and interpret the central limit theorem for sums.<\/li>\n<\/ul>\n<h2><strong>Module 8: Confidence Intervals<\/strong><\/h2>\n<ul>\n \t<li>Calculate and interpret confidence intervals for estimating a population mean and a population proportion.<\/li>\n \t<li>Interpret the Student\u2019s t probability distribution as the sample size changes.<\/li>\n \t<li>Discriminate between problems applying the normal and the Student\u2019s&nbsp;<em data-effect=\"italics\">t<\/em>&nbsp;distributions.<\/li>\n \t<li>Calculate the sample size required to estimate a population mean and a population proportion given a desired confidence level and margin of error.<\/li>\n<\/ul>\n<h2><strong>Module 9: Hypothesis Testing With One Sample<\/strong><\/h2>\n<ul>\n \t<li>Differentiate between Type I and Type II Errors<\/li>\n \t<li>Describe hypothesis testing in general and in practice<\/li>\n \t<li>Conduct and interpret hypothesis tests for a single population mean, population standard deviation known.<\/li>\n \t<li>Conduct and interpret hypothesis tests for a single population mean, population standard deviation unknown.<\/li>\n \t<li>Conduct and interpret hypothesis tests for a single population proportion.<\/li>\n<\/ul>\n<h2><strong>Module 10: Hypothesis Testing With Two Samples<\/strong><\/h2>\n<ul>\n \t<li>Classify hypothesis tests by type.<\/li>\n \t<li>Conduct and interpret hypothesis tests for two population means, population standard deviations known.<\/li>\n \t<li>Conduct and interpret hypothesis tests for two population means, population standard deviations unknown.<\/li>\n \t<li>Conduct and interpret hypothesis tests for two population proportions.<\/li>\n \t<li>Conduct and interpret hypothesis tests for matched or paired samples<\/li>\n<\/ul>\n<h2><strong>Module 11: The Chi Square Distribution<\/strong><\/h2>\n<ul>\n \t<li>Interpret the chi-square probability distribution as the sample size changes.<\/li>\n \t<li>Conduct and interpret chi-square goodness-of-fit hypothesis tests.<\/li>\n \t<li>Conduct and interpret chi-square test of independence hypothesis tests.<\/li>\n \t<li>Conduct and interpret chi-square homogeneity hypothesis tests.<\/li>\n \t<li>Conduct and interpret chi-square single variance hypothesis tests.<\/li>\n<\/ul>\n<h2><strong>Module 12: Linear Regression and Correlation<\/strong><\/h2>\n<ul>\n \t<li>Discuss basic ideas of linear regression and correlation.<\/li>\n \t<li>Create and analyze scatter plots.<\/li>\n \t<li>Create and interpret a line of best fit.<\/li>\n \t<li>Calculate and interpret the correlation coefficient.<\/li>\n \t<li>Use interpolation and extrapolation.<\/li>\n \t<li>Calculate and interpret outliers.<\/li>\n<\/ul>\n<h2><strong>Module 13: F-Distribution and the One-Way ANOVA<\/strong><\/h2>\n<ul>\n \t<li>Interpret the&nbsp;<em data-effect=\"italics\">F<\/em>&nbsp;probability distribution as the number of groups and the sample size change.<\/li>\n \t<li>Discuss two uses for the&nbsp;<em data-effect=\"italics\">F<\/em>&nbsp;distribution: one-way ANOVA and the test of two variances.<\/li>\n \t<li>Conduct and interpret one-way ANOVA.<\/li>\n \t<li>Conduct and interpret hypothesis tests of two variances.<\/li>\n<\/ul>\n<h2><strong>Module 14: Multiple and Logistic Regression<\/strong><\/h2>\n","rendered":"<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-254\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/2025\/2017\/07\/01225024\/outcomes.jpg\" alt=\"icon of a magnifying glass over a list\" width=\"200\" height=\"201\" \/><\/p>\n<p>The textbook&nbsp;content and assessments for Introduction to Statistics are aligned to the following learning outcomes.<\/p>\n<h2>Module 1: Sampling and Data<\/h2>\n<ul>\n<li>Recognize and differentiate between key terms.<\/li>\n<li>Apply various types of sampling methods to data collection.<\/li>\n<li>Create and interpret frequency tables.<\/li>\n<\/ul>\n<h2>Module 2: Descriptive Statistics<\/h2>\n<ul>\n<li>Display data graphically and interpret graphs: stemplots, histograms, and box plots.<\/li>\n<li>Recognize, describe, and calculate the measures of location of data: quartiles and percentiles.<\/li>\n<li>Recognize, describe, and calculate the measures of the center of data: mean, median, and mode.<\/li>\n<li>Recognize, describe, and calculate the measures of the spread of data: variance, standard deviation, and range.<\/li>\n<\/ul>\n<h2><strong>Module 3: Probability<\/strong><\/h2>\n<ul>\n<li>Understand and use the terminology of probability.<\/li>\n<li>Determine whether two events are mutually exclusive and whether two events are independent.<\/li>\n<li>Calculate probabilities using the Addition Rules and Multiplication Rules.<\/li>\n<li>Construct and interpret Contingency Tables.<\/li>\n<li>Construct and interpret Venn Diagrams.<\/li>\n<li>Construct and interpret Tree Diagrams.<\/li>\n<\/ul>\n<h2><strong>Module 4: Discrete Random Variables<\/strong><\/h2>\n<ul>\n<li>Recognize and understand discrete probability distribution functions, in general.<\/li>\n<li>Calculate and interpret expected values.<\/li>\n<li>Recognize the binomial probability distribution and apply it appropriately.<\/li>\n<li>Recognize the Poisson probability distribution and apply it appropriately.<\/li>\n<li>Recognize the geometric probability distribution and apply it appropriately.<\/li>\n<li>Recognize the hypergeometric probability distribution and apply it appropriately.<\/li>\n<li>Classify discrete word problems by their distributions.<\/li>\n<\/ul>\n<h2><strong>Module 5: Continuous Random Variables<\/strong><\/h2>\n<ul>\n<li>Recognize and understand continuous probability density functions in general.<\/li>\n<li>Recognize the uniform probability distribution and apply it appropriately.<\/li>\n<li>Recognize the exponential probability distribution and apply it appropriately.<\/li>\n<\/ul>\n<h2><strong>Module 6: Normal Distribution<\/strong><\/h2>\n<ul>\n<li>Recognize the normal probability distribution and apply it appropriately.<\/li>\n<li>Recognize the standard normal probability distribution and apply it appropriately.<\/li>\n<li>Compare normal probabilities by converting to the standard normal distribution.<\/li>\n<\/ul>\n<h2><strong>Module 7: The Central Limit Theorem<\/strong><\/h2>\n<ul>\n<li>Recognize central limit theorem problems.<\/li>\n<li>Classify continuous word problems by their distributions.<\/li>\n<li>Apply and interpret the central limit theorem for means.<\/li>\n<li>Apply and interpret the central limit theorem for sums.<\/li>\n<\/ul>\n<h2><strong>Module 8: Confidence Intervals<\/strong><\/h2>\n<ul>\n<li>Calculate and interpret confidence intervals for estimating a population mean and a population proportion.<\/li>\n<li>Interpret the Student\u2019s t probability distribution as the sample size changes.<\/li>\n<li>Discriminate between problems applying the normal and the Student\u2019s&nbsp;<em data-effect=\"italics\">t<\/em>&nbsp;distributions.<\/li>\n<li>Calculate the sample size required to estimate a population mean and a population proportion given a desired confidence level and margin of error.<\/li>\n<\/ul>\n<h2><strong>Module 9: Hypothesis Testing With One Sample<\/strong><\/h2>\n<ul>\n<li>Differentiate between Type I and Type II Errors<\/li>\n<li>Describe hypothesis testing in general and in practice<\/li>\n<li>Conduct and interpret hypothesis tests for a single population mean, population standard deviation known.<\/li>\n<li>Conduct and interpret hypothesis tests for a single population mean, population standard deviation unknown.<\/li>\n<li>Conduct and interpret hypothesis tests for a single population proportion.<\/li>\n<\/ul>\n<h2><strong>Module 10: Hypothesis Testing With Two Samples<\/strong><\/h2>\n<ul>\n<li>Classify hypothesis tests by type.<\/li>\n<li>Conduct and interpret hypothesis tests for two population means, population standard deviations known.<\/li>\n<li>Conduct and interpret hypothesis tests for two population means, population standard deviations unknown.<\/li>\n<li>Conduct and interpret hypothesis tests for two population proportions.<\/li>\n<li>Conduct and interpret hypothesis tests for matched or paired samples<\/li>\n<\/ul>\n<h2><strong>Module 11: The Chi Square Distribution<\/strong><\/h2>\n<ul>\n<li>Interpret the chi-square probability distribution as the sample size changes.<\/li>\n<li>Conduct and interpret chi-square goodness-of-fit hypothesis tests.<\/li>\n<li>Conduct and interpret chi-square test of independence hypothesis tests.<\/li>\n<li>Conduct and interpret chi-square homogeneity hypothesis tests.<\/li>\n<li>Conduct and interpret chi-square single variance hypothesis tests.<\/li>\n<\/ul>\n<h2><strong>Module 12: Linear Regression and Correlation<\/strong><\/h2>\n<ul>\n<li>Discuss basic ideas of linear regression and correlation.<\/li>\n<li>Create and analyze scatter plots.<\/li>\n<li>Create and interpret a line of best fit.<\/li>\n<li>Calculate and interpret the correlation coefficient.<\/li>\n<li>Use interpolation and extrapolation.<\/li>\n<li>Calculate and interpret outliers.<\/li>\n<\/ul>\n<h2><strong>Module 13: F-Distribution and the One-Way ANOVA<\/strong><\/h2>\n<ul>\n<li>Interpret the&nbsp;<em data-effect=\"italics\">F<\/em>&nbsp;probability distribution as the number of groups and the sample size change.<\/li>\n<li>Discuss two uses for the&nbsp;<em data-effect=\"italics\">F<\/em>&nbsp;distribution: one-way ANOVA and the test of two variances.<\/li>\n<li>Conduct and interpret one-way ANOVA.<\/li>\n<li>Conduct and interpret hypothesis tests of two variances.<\/li>\n<\/ul>\n<h2><strong>Module 14: Multiple and Logistic Regression<\/strong><\/h2>\n","protected":false},"author":395986,"menu_order":3,"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-23","chapter","type-chapter","status-publish","hentry"],"part":20,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/pressbooks\/v2\/chapters\/23","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/wp\/v2\/users\/395986"}],"version-history":[{"count":0,"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/pressbooks\/v2\/chapters\/23\/revisions"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/pressbooks\/v2\/parts\/20"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/pressbooks\/v2\/chapters\/23\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/wp\/v2\/media?parent=23"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/pressbooks\/v2\/chapter-type?post=23"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/wp\/v2\/contributor?post=23"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/nhti-introstats\/wp-json\/wp\/v2\/license?post=23"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}