Dive into a comprehensive 17-hour course on Applied Statistics, covering both descriptive and inferential statistics following a standard introductory curriculum. Learn from topics including data classification, statistical studies, frequency distributions, probability, discrete and continuous distributions, confidence intervals, hypothesis testing, and regression analysis. Explore concepts through lectures, utilizing the textbook "Beginning Statistics, 3rd ed" by Warren, Denley, and Atchley. Access supplementary materials like PowerPoint presentations and Excel data files to enhance your learning experience. Follow along with the extensive playlist of video lectures, covering everything from basic statistical concepts to advanced topics in hypothesis testing and regression analysis.
Overview
Syllabus
Statistics - 1.1 Intro to Statistics.
Statistics - 1.2 Classifying Data.
Statistics - 1.3.1 Introduction to Statistical Studies.
Statistics - 1.3.2 Observational Studies.
Statistics - 1.3.3 Experiments.
Statistics - 1.4 Critiquing a Published Study.
Statistics - 2.1 Frequency Distributions.
Statistics - 2.2.1 Displaying Qualitative Data.
Statistics - 2.2.2 Displaying Quantitative Data.
Statistics - 2.3 Analyzing Graphs.
Statistics - 3.1 Measures of Center.
Statistics - 3.2.1 Measures of Spread.
Statistics - 3.2.2 Empirical Rule and Chebyshev's Theorem.
Statistics - 3.3.1 Measures of Relative Position.
Statistics - 3.3.2 Box Plots and the 5-Number Summary.
Statistics - 3.3.3 Intro to Z-Scores.
Statistics - 4.1 Intro to Probability.
Statistics - 4.2 Addition Rule for Probability.
Statistics - 4.3 Multiplication Rule for Probability.
Statistics - 4.4 Permutations and Combinations.
Statistics - 4.5 Probability and Counting Practice.
Statistics - 5.1.1 Expected Value of Discrete Probability Distributions.
Statistics - 5.1.2 Variance and SD of Discrete Probability Distributions.
Statistics - 5.2 The Binomial Distribution.
Statistics - 5.3 The Poisson Distribution.
Statistics - 5.4.1 The Hypergeometric Distribution.
Statistics - 5.4.2 Binomial, Poisson or Hypergeometric?.
Statistics - 6.1 The Normal Distribution and Z-Scores.
Statistics - 6.2 Area Under a Normal Distribution.
Statistics - 6.3 Probabilities in a Normal Distribution.
Statistics - 6.4 Z-Scores in Reverse.
Statistics - 6.5 Approximating a Binomial Distribution With a Normal Distribution.
Statistics - 7.1 The Central Limit Theorem.
Statistics - 7.2 The Central Limit Theorem with Means.
Statistics - 7.3 The Central Limit Theorem with Proportions.
Statistics - 8.1.1 An Introduction to Confidence Intervals.
Statistics - 8.1.2 Estimating Population Means ( known).
Statistics - 8.1.3 Calculations With Estimating Population Means - known.
Statistics - 8.2 Student's t-Distribution.
Statistics - 8.3 Estimating Population Means ( Unknown).
Statistics - 8.4.1 Estimating Population Proportions.
Statistics - 8.4.2 Calculations With Estimating Population Proportions.
Statistics - 9.1 Comparing Two Population Means ( Known).
Statistics - 9.2.1 Comparing Two Population Means ( Unknown, Unequal Variances).
Statistics - 9.2.2 Comparing Two Population Means ( Unknown, Equal Variances).
Statistics - 9.3 Comparing Two Population Means ( Unknown, Dependent/Paired).
Statistics - 9.4 Comparing Two Population Proportions.
Statistics - 10.1.1 Introduction to Hypothesis Testing.
Statistics - 10.1.2 Writing Hypotheses.
Statistics - 10.1.3 Interpreting Conclusions to Hypothesis Tests.
Statistics - 10.1.4 Errors in Hypothesis Testing.
Statistics - 10.2.1 Hypothesis Testing for Population Means (σ known) - Right-Tailed.
Statistics - 10.2.2 Hypothesis Testing for Population Means (σ known) - Left-Tailed.
Statistics - 10.2.3 Hypothesis Testing for Population Means (σ known) - 2-Tailed.
Statistics - 10.3.1 Hypothesis Testing for Population Means (σ unknown) - 1-Tailed.
Statistics - 10.3.2 Hypothesis Testing for Population Means (σ unknown) - 2-Tailed.
Statistics - 10.4.1 Hypothesis Testing for Population Proportions - 1-Tailed.
Statistics - 10.4.2 Hypothesis Testing for Population Proportions - 2-Tailed.
Statistics - 11.1.1 Hypothesis Testing for 2 Sample Means (σ known) - 1-Tailed.
Statistics - 11.1.2 Hypothesis Testing for 2 Sample Means (σ known) - 2-Tailed.
Statistics - 11.2.1 Hypothesis Testing for 2 Sample Means (σ unknown) - Unequal Variances.
Statistics - 11.2.2 Hypothesis Testing for 2 Sample Means (σ unknown) - Equal Variances.
Statistics - 11.3 Hypothesis Testing for 2 Sample Means - Paired.
Statistics - 11.4 Hypothesis Testing for 2 Sample Proportions.
Statistics - 12.1.1 Scatter Plots and Correlation.
Statistics - 12.1.2 Determining Statistical Significance for the Pearson Correlation Coefficient.
Statistics - 12.2.1 The Least Squares Regression Line (LSRL).
Statistics - 12.2.2 Predicting With and Interpreting Values of the LSRL.
Statistics - 12.2.3 Creating and Analyzing a Linear Regression Model.
Statistics - 12.3.1 Prediction Intervals for Linear Regression.
Statistics - 12.3.2 Confidence Intervals for 0 and 1.
Statistics - 12.4 Multiple Regression.
Taught by
Kimberly Brehm
