ISI - PSYC 300 - Statistical Methods

Course Description

Statistical Methods is a survey of descriptive and inferential statistical concepts commonly used in the treatment of data in social science research. The understanding and application of the concepts will be emphasized. Topics include: measures of central tendency, measures of variability, correlation methods, hypothesis testing and simple analysis of variance.

This course is designed to provide students with a basic understanding of the fundamentals of statistics. The emphasis will be on understanding, application, and problem solving, not on extensive computations and the memorization of formulas. We will do computations by hand with small data sets. We will not use statistical software, though the textbook discusses such analyses. The concepts considered in this course are those related to the representation of information (descriptive statistics) and those concepts related to drawing conclusions based on sample data (inferential statistics, including probability, the normal distribution, and hypothesis testing, effect sizes, and confidence intervals—single-sample t, related-samples t, independent-samples t, ANOVA, correlations, chi-square).

LC State students: cross-listed with ECON 300 Statistical Methods, SS 300 Statistical Methods.

Learner Outcomes

Upon completion of the course, the student:

• will be familiar with the various scales of measurement;
• will be familiar with the basic shapes of frequency distributions;
• will be familiar with the calculations, uses, and interpretations of the three measures of central tendency;
• will be familiar with the calculations, uses, and interpretations of measures of variability;
• will be familiar with the normal curve and using the normal curve table to solve application problems;
• will be familiar with the basic theory behind hypothesis testing, including the concepts of rejecting, or failing to reject, the null hypothesis (statistical significance);
• will be able to follow the steps to carry out different types of t-tests and interpret the results;
• will be familiar with confidence intervals and effect sizes and their interpretations;
• will be familiar with the concepts of Type I and Type II errors;
• will be able to follow the steps to carry out a one-way ANOVA and interpret the results;
• will demonstrate an understanding of correlation, including the limitations of conclusions that can be drawn;
• will be able to follow the steps to carry out chi-square goodness-of-fit and chi-square test of independence analyses and interpret the results;
• will be able to select the appropriate inferential analysis for various situations.

Required Course Materials

Carlson, K. A., & Winquist, J. R. (2022). An introduction to statistics: An active learning approach (3rd ed.). Sage. (DO NOT order a newer edition if available)

View Course Syllabus

Expected Course Timeline

Most ISI courses are designed so that students can complete them within 3 months to 1 year. If you are attempting to complete a course more quickly than this, please contact ISI to explore your options.

Sponsor Institution

Credits earned for this course are included in a LC State transcript.

This is an INDEPENDENT STUDY IN IDAHO course

To learn about program and refund policies, visit www.uidaho.edu/isi.

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