Topical Outline with Specific Course Objectives
- Descriptive Statistics
- Calculate and interpret the various descriptive measures for centrality and dispersion.
- Determine potential outliers of data sets and understand how they affect the various numerical measures.
- Analyze and/or compare different sets of data using graphs, charts, tables, and numerical measures, and write about them in clear and precise sentences using statistical vocabulary.
- Demonstrate an understanding of the different types of distributions.
- Organize and display data by means of various tables, charts, and graphs.
- Define and use the basic terminology of statistics.
- Simple Linear Regression and Correlation
- Find and interpret the sample correlation coefficient (r) to determine the strength and direction of the linear relationship between predictor and response variables.
- Use scatter plots to determine if outliers are present and if data can be represented by a simple linear regression model.
- Find the simple linear regression model and be able to interpret the slope and y-intercept.
- Use r-squared to determine if a simple linear regression model is a strong predictor.
- Predict values of “y” using the simple linear regression model
- Normal Probability Distribution
- Calculate and interpret a z-score as a measure of relative standing and use it as it applies to the normal model.
- Understand the Normal Probability Distribution and be able to determine appropriate areas under a normal curve.
- Use the 68-95-99.7 Rule (Empirical Rule) to find probabilities on an approximately normal or bell-shaped distribution.
- Use a histogram or normal probability plot, determine if a sample comes from a normally distributed population.
- Fundamentals of Probability
- Understand and apply basic rules of probability.
- Understand and apply the Binomial Probability Distribution.
- Identify the random variable involved in a statistical problem and distinguish between: categorical vs quantitative, discrete vs continuous, and binomial vs normal.
- Inferential Statistics
- Demonstrate at least a rudimentary understanding of basic sample and experimental design (i.e. randomness, bias, etc. ).
- Understand and apply sampling distribution models for sample proportions and sample means
- Understand and apply the Central Limit Theorem.
- Estimate means and proportions using confidence intervals for one and two populations.
- Be able to perform hypothesis tests on means and proportions for one and two populations.
- Determine and interpret p-values.
- Demonstrate competency in the use of technology, including graphing calculator and/or statistical computer software as it applies to topics I – V.
Department Policies
- Graphing Calculator Required
- Comprehensive Final