***This is a course guideline. Students should contact instructor for the updated information on current course syllabus, textbooks, and course content***
Prerequisites: MATH 3338 Probability
Course Description: Basic principles for statistical inference with practical applications of data. Includes point estimation, confidence intervals, hypothesis testing, ANOVA and simple linear regression. Includes use of statistical software.
Textbook: Dunlop, Tamhane, Statistics and Data Analysis: From Elementary to Intermediate, 1st edition, Pearson, 2000. ISBN: 978-0130225788
- Review of Probability (1 week)
- Summarizing and Exploring Data (1 week)
- Introduction to random variables
- Distributions of random variables
- Graphical displays of data
- Sampling Distribution of Statistics (1 week)
- Χ2 –distribution
- Point Estimation (1 week)
- Methods of Point Estimation
- Inference for Single Samples (2 weeks)
- Confidence interval for one sample mean
- Confidence interval for one sample proportion
- Confidence interval for variance
- Hypothesis Tests for one sample mean and proportion
- Inferences for Two Samples (2 weeks)
- Inference for mean of matched paired data
- Inference for two independent means
- Inference for two proportions
- Simple Linear Regression and Correlation (2 weeks)
- Inference for correlation
- Introduction to simple linear regression
- Inference for regression parameters
- Inference for prediction
- Analysis of Variance (ANOVA) (1 week)
- Inferences for Count Data (2 weeks)
- Chi-square test for goodness of fit
- Chi-square test for independence
- Nonparametric Statistical Methods (1 week
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