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Statistical Analysis (MATH 1150)

Credits: 4
Lecture Credits: 4.00

Description: This course is an introduction to the fundamental concepts of descriptive and inferential statistics, with an emphasis on applications. Course content includes: sample surveys and experiment designs; graphic presentation of data; measures of central tendency, variation and position; exploratory data analysis; introductory probability; random variables and probability distributions; binomial and normal distributions; the Central Limit Theorem; estimation; hypothesis testing; comparisons of two populations; correlation and regression; applications of chi-square; and analysis of variance (ANOVA). The course assumes that the student is familiar with basic computer applications software. Statistical software and/or statistical graphing calculators are introduced and used extensively.

Topical Outline:

1. Types of an measurement of data
2. Sampling methods, sample surveys and experiment designs
3. Probability and probability distributions
4. Hypothesis testing and inferences from one and two samples
5. Correlation and regression
6. Applications of chi-square and analysis of variance

Learning Outcomes:
1. Describe data graphically and numerically
2. Calculate correlation coefficients and regression equations
3. Formulate questions and develop null and alternative hypotheses
4. Analyze the data and draw conclusions based on probability



MATH 1110 or MATH 1116 or MATH 1119 or MATH 1125. Completion of CSCI 1100 or equivalent computer experience is also recommended.

MnTC: Goal 4