## Statistics 204## Elementary Statistics |

An introduction to data analysis and statistics, including exploratory data analysis, inference for numerical and categorical variables, and regression.

*Textbook*

- Lock home page
- Lock data sets (csv files)
- Wiley student companion site
- R package Lock5Data reference manual

- Stat 204 MWF Spring 2020 revised schedule

- R
*(Install R before installing RStudio)* - RStudio
- Google Chrome

1.1. The Structure of Data

1.2. Sampling from a Population

1.3. Experiments and Observational Studies

*2. Describing Data*

2.1. Categorical Variables

2.2. One Quantitative Variable: Shape and Center

2.3. One Quantitative Variable: Measures of Spread

2.4. Boxplots and Quantitative/Categorical Relationships

2.5. Two Quantitative Variables: Scatterplot and Correlation

2.6. Two Quantitative Variables: Linear Regression

2.7. Data Visualization and Multiple Variables

*Unit B. Understanding Inference*

*3. Confidence Intervals*

3.1. Sampling Distributions

3.2. Understanding and Interpreting Confidence Intervals

3.3. Constructing Bootstrap Confidence Intervals

3.4. Bootstrap Confidence Intervals using Percentiles

*4. Hypothesis Tests*

4.1. Introducing Hypothesis Tests

4.2. Measuring Evidence with P-values

4.3. Determining Statistical Significance

4.4. A Closer Look at Testing

4.5. Making Connections

*Unit C. Inference with Normal and t-Distributions*

*5. Approximating with a Distribution*

5.1. Hypothesis Tests Using Normal Distributions

5.2. Confidence Intervals Using Normal Distributions

*6. Inference for Means and Proportions*

*6.1. Inference for a Proportion*

6.1-D. Distribution of a Sample Proportion

6.1-CI. Confidence Interval for a Single Proportion

6.1-HT. Test for a Single Proportion

*6.2. Inference for a Mean*

6.2-D. Distribution of a Sample Mean

6.2-CI. Confidence Interval for a Single Mean

6.2-HT. Test for a Single Mean

*6.3. Inference for a Difference in Proportions*

6.3-D. Distribution of Differences in Proportions

6.3-CI. Confidence Interval for a Difference in Proportions

6.3-HT. Test for a Difference in Proportions

*6.4. Inference for a Difference in Means*

6.4-D. Distribution of Differences in Means

6.4-CI. Confidence Interval for a Difference in Means

6.4-HT. Test for a Difference in Means

*6.5. Paired Difference in Means*

6.5. Paired Difference in Means

*Unit D. Inference for Multiple Parameters*

*7. Chi-Square Tests for Categorical Variables*

7.1. Testing Goodness-of-Fit for a Single Categorical Variable

7.2. Testing for an Association between Two Categorical Variables

*8. ANOVA to Compare Means*

8.1. Analysis of Variance

8.2. Pairwise Comparisons and Inference after ANOVA

*9. Inference for Regression*

9.1. Inference for Slope and Correlation

9.2. ANOVA for Regression

9.3. Confidence and Prediction Intervals

*10. Multiple Regression*

10.1. Multiple Predictors

10.2. Checking Conditions for a Regression Model

10.3. Using Multiple Regression

*P. Probability Basics*

P.1. Probability Rules

P.2. Tree Diagrams and Bayes' Rule

P.3. Random Variables and Probability Functions

P.4. Binomial Probabilities

P.5. Density Curves and the Normal Distribution

*Professor*

If you would like to talk with me in addition to the interactions generated during those hours, please make an appointment to see me in my office (WL120), either when you see me in class or in the hallways or in my office, or by email (cparrish@sewanee.edu), or by voice mail message (x1333).

*Statistics Study Hall and Tutoring*

The Library has kindly made the Mac Lab, G31, available for statistics students and friends from Monday through Thursday evenings, from 7 to 9 pm. Statistics tutors will be available for students from all sections of Stat 204 on Monday, Tuesday, and Wednesday evenings in the same location from 7:30 to 9 pm. Our statistics tutors this semester are

Allison Bernardino & Szonja Szurop - Mondays

Tillman James & Jennifer Echavarria - Tuesdays

Jordan Brewer & Kate Baker- Wednesdays

They will be available to help you come to grips with theoretical and computational aspects of statistics. Drop by to discuss statistics
with the tutors and other students, or just to work on your classwork and homework in a supportive environment, with nice computers, and
easy access to knowledgeable statistics students.

*Grading*

Every assignment in this class has a specific due date. Normally, work submitted after its due date will not count for a grade. Exceptions may be granted for officially sanctioned reasons, such as being out of town with a university athletic team, but you must obtain permission beforehand. Otherwise, late work will not count for a grade and make-up quizzes and exams will not be given.