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This course explores the fundamentals of statistical methods and reasoning. Topics include descriptive methods, data gathering, probability, interval estimation, significance tests, one- and two-sample problems, categorical data analysis, correlation and regression. The instructor will demonstrate the use of spreadsheets and statistical software to analyze and interpret data. Examples are drawn from a variety of fields including biology, business and marketing. While not too mathematically rigorous for the novice, the course provides some mathematical detail to illustrate basic concepts. No prior background in calculus or statistics is required.

Skills Needed

• To be successful in this class all students should have working knowledge of Google’s G Suite or Microsoft Office, proper email etiquette, and essential understanding of Canvas.

Learning Outcomes

At the conclusion of the course, you should be able to
• Display sample data using histograms and similar graphing techniques
• Analyze raw data, whether grouped or ungrouped, by calculating sample statistics including mean, median, variance, standard deviation and range
• Determine the rank of an individual piece of data by determining the particular percentile to which the data belongs
• Solve a variety of problems related to normal distributions
• Find confidence intervals for population mean and proportions and calculate sample sizes required for various confidence levels
• Set-up, calculate and analyze one-sample hypothesis tests of population means and proportions
• Differentiate between situations involving one population and those involving two
• Plot scatter diagrams of paired data and use the principles of linear regression and correlation to analyze such data, predict values of a dependent variable from the regression equation and determine whether the correlation is sufficient to make the regression equation a useful predictor
• Test for independence of row and column characteristics (and homogeneity) in two-way tables
• Understand and use One-Way ANOVA

Topics Include

• Orientation
• Descriptive Statistics
• Probability
• Hypothesis Testing
• Estimation
• Inference about Two Populations
• Correlation
• The Chi Squared Distribution
• ANOVA

Notes

This is not a course that is calculus based and only a beginning to intermediate algebra level of mathematical ability is required.

TI-83, TI-83 plus, TI-84 plus or virtual TI-83 (free and available on the www.drrobertknight.com (Links to an external site.)

Virtual TI-83.html TI-83 Class Notes ClassNotes.pdf
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