# MAT 175 Introductory Statistics

Math 175 Exit Skills

1. Understand the difference between inferential and descriptive statistics. Use the various sampling techniques including random sampling, stratified, random, cluster, and systematic sampling.
2. Use graphs to describe and interpret data sets including frequency histogram, frequency polygon, ogive, and pie charts.
3. Calculate measures of central tendency (mean, median and mode), measures of variation (range, variance, standard deviation), and measures of position (quartiles and percentiles).
4. Use the Fundamental Counting Rule, combinations and permutations to calculate probabilities.
5. Understand basic terminology and concepts of probability including sample spaces, complementary events, independent events and mutually exclusive events.
6. Calculate probabilities and expected values using the addition rule, multiplication rule and conditional probability.
7. Know properties of the Binomial Distribution and be able to calculate binomial probabilities.
8. Know properties of the Normal Distribution including the Empirical Rule. Calculate probabilities using the Normal Distribution. Use the central limit theorem and approximate the Binomial Distribution using the Normal Distribution.
9. Calculate confidence interval estimates for the mean of a population, for proportions and for variance. Determine sample size needed to obtain confidence levels.
10. Perform hypothesis tests for mean, proportion, variance, difference between two means and difference between proportions.
11. Test differences in three or more means using one-way analysis of variance (ANOVA).
12. Use correlation and perform a simple linear regression.
13. Use a scientific calculator and/or computer software to perform statistical analyses and assist in decision-making.

Objectives

1. Employ sampling techniques to collect data and summarize data using graphs and descriptive statistics.
2. Solve counting and probability applications.
3. Determine whether or not a variable conforms to a particular probability distribution including the binomial distribution, normal distribution, F-distribution or t-distribution.
4. Compute confidence interval estimates and perform hypothesis tests pertaining to one and two samples. Test multiple samples via analysis of variance.
5. Perform a linear regression analysis.

Revised April 5, 2013

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