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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 (𝜎 known)

Statistics - 8.1.3 Calculations With Estimating Population Means - 𝜎 known

Statistics - 8.2 Student's t-Distribution

Statistics - 8.3 Estimating Population Means (𝜎 Unknown)

Statistics - 8.4.1 Estimating Population Proportions

Statistics - 8.4.2 Calculations With Estimating Population Proportions

Statistics - 9.1 Comparing Two Population Means (𝜎 Known)

Statistics - 9.2.1 Comparing Two Population Means (𝜎 Unknown, Unequal Variances)

Statistics - 9.2.2 Comparing Two Population Means (𝜎 Unknown, Equal Variances)

Statistics - 9.3 Comparing Two Population Means (𝜎 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 𝛽0 and 𝛽1

Statistics - 12.4 Multiple Regression

Description:

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.

Applied Statistics

Kimberly Brehm

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#Mathematics #Statistics & Probability #Hypothesis Testing #Descriptive Statistics #Inferential Statistics #Data Science #Graph Analysis #Computer Science #Machine Learning #Regression Models #Data Classification #Applied Statistics

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