STA 126: Introductory Statistics

Mercer University

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Textbook

Sullivan, M. III. (2024). Statistics: Informed decisions using data (7th edition). Pearson.

Lecture Notes

Part I

•  Introduction to R – R console, RStudio
•  Introduction to Statistics – Data collection
•  Sampling Methods – simple random sample, stratified sample, systematic sample, cluster sample
•  Research Methods – obervational study, experiment
•  Categorical Data – frequency table, relative frequency, bargraph, pie chart
•  Numerical Data – histogram, steam-and-leaf plot, boxplot, numeric summaries

Part II

•   Linear Regression – Linear correlation coefficient, linear regression line
•   Probability Basics – Sample space, event, intersection, union, complement, odds, addition rule.
•   Conditional Probability – Conditional probability, diagnostic test, independent events
•   Counting Principles – Basic counting principle, factorial, combination, permutation.

Part III

•   Random Variables – Random variables, discrete probability distribution
•   Binomial Random Variables – Binomial experiment, binomial distribution
•   Normal Random Variables – Normal distribution
•   Sampling Distribution – Central Limit Theorem

Part IV

•   Estimate Population Proportions – Confidence intervals, confidence level, margin of error
•   Hypothesis Test: Population Proportion – Null hypothesis, alternative hypothesis, significance level, p-value
•   Types of Errors in Hypothesis Test – Type I error, Type II error
•   Estimate Population Means – t-distribution, degree of freedom
•   Hypothesis Test: Population Mean

Appendix

• Lockdown Browser and Posit Cloud
• More Delicate Examples on Graphs
• Working with MyLab’s Datasets
• Other Resources
  • SimpleR: Using R for Introductory Statistics by John Verzani. 0.4 edition, CUNY, 2002.