Baton Rouge Community College Academic Affairs Master Syllabus

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Baton Rouge Community College
Academic Affairs Master Syllabus
Date Approved or Revised: February 28, 2012
Course Name: Descriptive Statistics in Psychology LAB
Course Number: PSYC 206L
Lecture Hrs. 0
Lab Hrs. 2
Credit Hrs. 1
Course Description:
Introduces descriptive and inferential statistics. Includes frequency
distributions, measures of variability, normal curve, percentiles, regression, probabilities, t-Tests, and
analysis of variance through computer-based programming.
Prerequisites: MATH 101/110 and PSYC 201
Co-requisites: PSYC 206
Suggested Enrollment Cap: 30
Note: Not transferable as MATH 202 Basic Statistics I or MATH 203 Basic Statistics II
Learning Outcomes: Upon successful completion of this course, the students will be able
to:
1. Will teach students theories and concepts related to statistical analysis
2. Will enhance mathematical and computer skills related to statistics
3. Students will be able to distinguish between descriptive versus inferential statistics.
4. Will teach students to analyze statistical formulas though perception, calculation,
and computer computations.
5. Students will be able to compute percentiles, correlation coefficients, t-Tests,
Analysis of Variance (ANOVA), and Chi-Square.
Assessment Measures: Assessment of all learning outcomes will be measured using the
following methods:
The student will demonstrate his or her progress toward these objectives through
the use and application of SPSS computer based programs, as well as,
completion of unit examinations, quizzes, class discussions, final exam, projects,
and/or written homework assignments
Information to be included on the Instructors’ Course Syllabi:

Disability Statement: Baton Rouge Community College seeks to meet the needs of its
students in many ways. See the Office of Disability Services to receive suggestions for
disability statements that should be included in each syllabus.

Grading: The College grading policy should be included in the course syllabus. Any
special practices should also go here. This should include the instructor’s and/or the
department’s policy for make-up work. For example in a speech course, “Speeches not
given on due date will receive no grade higher than a sixty” or “Make-up work will not
be accepted after the last day of class.”

Attendance Policy: Include the overall attendance policy of the college. Instructors
may want to add additional information in individual syllabi to meet the needs of their
courses.

General Policies: Instructors’ policy on the use of things such as beepers and cell
phones and/or hand held programmable calculators should be covered in this section.

Cheating and Plagiarism: This must be included in all syllabi and should include the
penalties for incidents in a given class. Students should have a clear idea of what
constitutes cheating in a given course.

Safety Concerns: In some programs this may be a major issue. For example, “No
student will be allowed in the safety lab without safety glasses.” General statements
such as, “Items that may be harmful to one’s self or others should not be brought to
class.”

Library/ Learning Resources: Since the development of the total person is part of our
mission, assignments in the library and/or the Learning Resources Center should be
included to assist students in enhancing skills and in using resources. Students should
be encouraged to use the library for reading enjoyment as part of lifelong learning.
Expanded Course Outline:
Week 1: Introduction to Statistics (topics include: hypothesis, variables, and scales of measurement)
Week 2: Frequency Distribution (topics include: ranked and frequency distributions, apparent and real
limits, and relative and cumulative relative frequency)
Week 3: Graphs (topics include: frequency histogram, frequency polygon, relative and cumulative
frequency polygon, cumulative relative frequency polygon, cumulative percent polygon,
and stem-and-leaf diagrams)
Week 4: Measures of Central Tendency (topics include: mean, mode, median, frequency distributions
and box-plots)
Week 5: Measures of Variability (topics include: range, mean deviation, variance, and standard
deviation)
Week 6: Scales Scores and Standard Scores (topics include: adding and subtracting of constants and
division and multiplication by constants)
Week 7: The Normal Curve (topics include: normal curve, proportions vs. percentage, and percentile)
Week 8: Correlation (topics include: correlation coefficient and covariance)
Week 9: Regression (topics include: predictions vs. linear regression, z-scores, regression line and
standard error of estimates)
Week 10: Probability Theory and Sampling (topics include: probabilities and sampling, standard error
of the mean, The Central Limit Theorem, and 1-Test)
Week 11: Experimental Design (topics include: development of hypotheses, identifying variables,
factors in experimental design, and statistical significance)
Week 12: t-test (topics include: single sample t tests, t tests between two independent sample means, t
tests for correlated samples and power and t tests)
Week 13: One-way Analysis of Variance (topics include: hypothesis testing, computation of mean
square between and within groups, and F test)
Week 14: Two-Way Analysis of Variance (topics include: main effects, interaction, computations of
sums of squares, computations of degrees of freedom, computation of mean squares,
computation of F Ratios, significance of main effects and significance of interaction)
Week 15: Chi-Square and Other Nonparametric Statistics (topics include: The Mann-Whitney U Test,
The Wilcoxin T Test, and The Kruskal-Wallis Test)
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