PSYC 2317: Statistical Methods in Psychology
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Course Student Learning Outcomes (CSLOs) |
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1. Compute and interpret empirical and theoretical probabilities. |
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Learning Objectives for CSLO 1: Compute and interpret empirical and theoretical probabilities. |
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1.1 Define probability |
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1.2 Calculate the probability of a specific outcome as a proportion, decimal, and percentage |
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1.3 Calculate probabilities of specific values in data sets arranged in frequency distributions tables and graphs |
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1.4 Determine probabilities associated with specific z-scores in the unit normal table |
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1.5 Determine probabilities associated with specific scores in a normal distribution |
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Key terms: probability, random sample, independent random sample, unit normal table |
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Learning Objectives for CSLO 2: Define and explain the characteristics of data based on their reliability, validity, and scales of measurement. |
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2.1 Explain the use of correlations in the determination of the reliability of a measurement procedure |
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2.2 Explain the use of correlations in the determination of the validity of a measurement procedure |
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2.3 Compare the characteristics of nominal, ordinal, interval, and ratio scales of measurement |
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2.4 Compare discrete and continuous variables |
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Key terms: construct, operational definition, discrete variable, continuous variable, nominal scale, ordinal scale, interval scale, ratio scale, reliability, validity |
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Learning Objectives for CSLO 3: Interpret visual representations of data, such as graphs and tables. |
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3.1 Determine the appropriate type of graph for a set of data based on scale type (nominal, ordinal, interval, ratio) |
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3.2 Explain the advantages and disadvantages of grouped frequency distributions |
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3.3 Construct frequency distribution tables and graphs |
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3.4 Make inferences about variables based on data based on frequency distribution tables and graphs |
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3.5 Categorize distributions as symmetrical, positively skewed, and negatively skewed |
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Key terms: symmetrical distribution, positive skew, negative skew, normal distribution, real limits |
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Learning Objectives for CSLO 4: Compute and interpret descriptive statistics, such as mean, median, and mode; standard deviation and range; and transformed scores. |
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4.1 Compute mean, median, mode, standard deviation, range, and z-scores using data sets |
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4.2 Compute mean, median, mode, standard deviation, range, and z-scores using data arranged in frequency distribution tables and graphs |
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4.3 Interpret mean, median, mode, standard deviation, range, and z-scores |
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4.4 Explain the relationships among measures of central tendency and distribution shapes |
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4.5 Describe the characteristics of the mean and how it is affected by changes in the data from which it is calculated |
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4.6 Describe the uses, advantages, and disadvantages of mean, median, and mode |
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4.7 Describe the uses, advantages, and disadvantages of range and standard deviation |
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4.8 Explain the difference between measures of variability in populations and samples |
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4.9 Describe the relationship between score transformations and measures of variability |
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4.10 Explain the role of measures of central tendency and variability in the reporting of research results in scientific journals |
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4.11 Compute standard score transformations using z-scores |
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4.12 Determine scores from z-scores and vice-versa |
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4.13 Describe the characteristics of z-score distributions |
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4.14 Explain the uses of z-scores and their advantages over raw scores |
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Key terms: descriptive statistics, central tendency, mean, median, mode, multimodal, bimodal, variability, range, variance, standard deviation, degrees of freedom, z-score |
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Learning Objectives for CSLO 5: Compute and interpret inferential statistics and tests, such as z test, t test, ANOVA, and Chi-Square. |
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5.1 Compute t tests, z tests, ANOVA, and chi-square |
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5.2 Interpret the results of z tests, t tests, ANOVA, and chi-square |
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5.3 Describe the uses and limitations of z tests, t tests, ANOVA, and chi-square |
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5.4 Describe the various uses of the chi-square goodness-of-fit test |
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5.5 Explain the difference between parametric and nonparametric statistical tests |
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5.6 Calculate expected frequencies based on a chi-square test |
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Key terms: inferential statistics, degrees of freedom, multivariate analysis of variance, independent samples, dependent samples, repeated measures tests, ANOVA, z test, t test, chi-square test |
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Learning Objectives for CSLO 6: Calculate, evaluate, and interpret simple linear correlation/regression. |
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6.1 Create scatterplots |
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6.2 Interpret scatterplots |
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6.3 Explain the meaning of a correlation’s strength and direction |
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6.4 Compute Pearson correlations |
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6.5 Explain the uses of Pearson, Spearman, and point biserial correlations |
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6.6 Interpret correlations using the concepts of causation, range restriction, and outliers |
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6.7 Explain the uses of the coefficient of determination |
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6.8 Describe the process of hypothesis testing as it applies to correlations |
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6.9 Explain the role of regression equations in prediction |
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6.10 Use the least-squares solution to determine how well a line fits a given set of data points |
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6.11 Describe the use of regression as an inferential statistic |
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Key terms: correlation, coefficient of determination, effect size, linear relationship, regression, regression line, least squares solution |
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Learning Objectives for CSLO 7: Construct and interpret confidence intervals. |
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7.1 Explain the use of a confidence interval to describe the size of a treatment effect |
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7.2 Describe the factors that influence the width of a confidence interval |
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7.3 Construct confidence intervals |
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7.4 Interpret confidence intervals |
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Key terms: confidence interval |
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Learning Objectives for CSLO 8: Examine, analyze, and compare various sampling distributions. |
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8.1 Explain the relationship between sample size and the distribution of sample means |
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8.2 Describe the characteristics of the distribution of sample means |
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8.3 Determine the probability of a sample mean using z-scores |
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8.4 Compute the standard error of the mean |
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Key terms: sample, population, distribution of sample means, sampling distribution, central limit theorem, standard error of the mean |
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Learning Objectives for CSLO 9: Formulate, perform, and interpret hypotheses tests. |
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9.1 Describe the steps involved in using inferential statistics to test a hypothesis |
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9.2 Use inferential statistics to perform hypothesis tests |
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9.3 Explain the implications of rejecting and failing to reject a null hypothesis |
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9.4 Describe the relationship between sample size and the power of a statistical test |
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Key terms: hypothesis testing, null hypothesis, alternative hypothesis, power of a statistical test, Type I error, Type II error, on-tailed test, two-tailed test, alpha level, level of significance, critical region, statistical significance, test statistic |
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Learning Objectives for CSLO 10: Identify the appropriate statistical analyses for given research problems, questions, hypotheses, and data sets. |
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10.1 Choose the appropriate inferential test or tests for a given research problem, question, hypothesis, or data set |
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10.2 Explain why a given inferential test is appropriate or inappropriate for a given research problem, question, hypothesis, or data set |
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Key terms: None |
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Learning Objectives for CSLO 11: Apply statistical knowledge to the interpretation of psychological research. |
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11.1 Explain a research study’s methods, statistical analyses, results, and conclusions |
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11.2 Explain the relationships among a research study’s methods, statistical analyses, results, and conclusions |
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Key terms: None |
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Learning Objectives for CSLO 12: Explain features and purpose of statistical software packages. |
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12.1 Describe the Statistical Package for the Social Sciences (SPSS) |
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12.2 Explain the advantages of using statistical software |
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Key terms: None |