MCCCD Program Description

Introduction to Statistics with Lab

Course: PSY230WL

First Term: 2023 Fall

Lec + Lab 4.0 Credit(s) 5.0 Period(s) 5.0 Load
Subject Type: Academic
Load Formula: T- Lab Load

Description: An introduction to basic concepts in descriptive and inferential statistics, with emphasis upon application to psychology. Consideration given to the methods of data collection, sampling techniques, graphing of data, use of statistical software, and the statistical evaluation of data collected through experimentation. Required of psychology majors.

MCCCD Official Course Competencies
1. Organize data for entry or analysis using appropriate tools (e.g., calculator, statistical software). (I, II) 2. Explain how statistics are used within the scientific method. (I, II, III, IV) 3. Use an appropriate scale of measurement to operationalize a construct of interest. (I, II, III, IV) 4. Evaluate the data collection, statistical analyses, interpretation, and presentation of research results in a variety of contexts. (I, II, III, IV) 5. Use the appropriate statistical test based on the research design (research question, data type, and number of variables). (I, II, III, IV) 6. Assess the practical implications and ethical considerations of statistical analysis in a variety of contexts beyond the classroom. (I, II, III, IV) 7. Communicate statistical concepts and research results using both technical (American Psychological Association [APA] format) and non-technical language. (I, II, III, IV) 8. Assess accuracy of data (including consideration of missing data and outliers) using an appropriate tool (e.g., calculator, graph, statistical software). (I, II, IV) 9. Verify potential violation of assumptions of a statistical test to determine the validity and reliability of results. (I, II, IV) 10. Compute descriptive statistics (including frequency distributions, measures of central tendency, measures of variability, and z-scores) and inferential statistics (including t-tests, analysis of variance, correlation/regression, and chi-square) both by hand and using statistical software. (II, IV) 11. Interpret descriptive statistics (including frequency distributions, measures of central tendency, measures of variability, and z-scores) and inferential statistics (including t-tests, analysis of variance, correlation/regression, and chi-square) using appropriate resources (e.g., results and output). (II, IV) 12. Explain the role of probability as the cornerstone of statistics. (III) 13. Utilize effect size, confidence intervals, power, and p-values to explain the statistical and practical significance of a statistical analysis. (IV)
MCCCD Official Course Competencies must be coordinated with the content outline so that each major point in the outline serves one or more competencies. MCCCD faculty retains authority in determining the pedagogical approach, methodology, content sequencing, and assessment metrics for student work. Please see individual course syllabi for additional information, including specific course requirements.

MCCCD Official Course Outline
I. Fundamentals of statistics A. Population and samples B. Sampling C. Research designs D. Variables E. Evaluating sources 1. Introduction to statistical software 2. Organizing data 3. Statistical test selection 4. Data entry 5. Data analysis 6. Assessing data accuracy F. Ethics II. Descriptive statistics A. Organization and display of data 1. Frequency distributions (tables and graphs) 2. Shapes of distributions B. Measures of central tendency 1. Mean 2. Median 3. Mode C. Measures of variability 1. Variance 2. Standard deviation D. Z-scores E. Percentiles III. Probability A. Central limit theorem B. Relationship between probability and inferential statistics IV. Inferential statistics A. Relationship between the normal distribution and z-scores B. Hypothesis testing C. Test statistics 1. Z-test 2. Single-sample t-test 3. Independent t-test 4. Dependent t-test 5. Analysis of variances 6. Correlation/Regression 7. Chi-square D. Interpreting statistical results 1. Statistical significance (p-value) 2. Practical significance a. Effect size b. Power c. Confidence intervals

MCCCD Governing Board Approval Date: May 24, 2022

All information published is subject to change without notice. Every effort has been made to ensure the accuracy of information presented, but based on the dynamic nature of the curricular process, course and program information is subject to change in order to reflect the most current information available.