Course Description –
Students will be introduced to the analysis of quantitative data in the behavioral sciences. Students will learn the utilization of descriptive and inferential statistics as they relate to the interpretation of data using various analytical tools.

Pre-requisite –

  • MATH 1111 College Algebra or MATH 1101 Math Modeling

Required Text –

  • Salkind, N.J. (2014). Statistics for People Who (Think They) Hate Statistics: 5th Ed. Thousand Oaks, CA: SAGE
  • ISBN-13: 9781452277714

Course Learning Outcomes –

  • Define the term statistics
  • Discuss the difference between descriptive and inferential statistics
  • Explain “measures of central tendency”
  • Define the mean, median, and mode
  • Compute variability using the formula for range
  • Compute variability using the formula for standard deviation
  • Computer variability using the formula for variance
  • Explain skewness and kurtosis
  • Compute the coefficient of determination and coefficient of alienation
  • Identify different types of correlation coefficients
  • Explain the difference between a sample and a population
  • Define the null and the research hypotheses
  • Explain the purpose of the null hypothesis
  • Define what a normal or bell-shaped curve is
  • List the characteristics of the normal curve
  • Define what is meant by a standard score
  • Explain and interpret a z score
  • Define Type I error
  • Define Type II error

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