Community College of Rhode Island

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Math 1475: Statistics for the Social Sciences

3 Credit Course
Offered in Lecture Format
Prerequisite required (MATH 1430)

SYLLABUS

  • I. GENERAL CONCEPTS
    • A. Population and Samples
      • 1. Target population versus sampled population
      • 2. Census versus sampling
      • 3. Population parameters and sampling statistics
      • 4. Types of samples
    • B. Random variables
      • 1. Discrete and continuous variables
      • 2. Numeric and categorical variables
    • C. Measuring Scales
      • 1. Nominal
      • 2. Ordinal
      • 3. Interval
      • 4. Ratio
  • II. PRESENTATION OF DATA
    • A. Stem and leaf plot
    • B. Single and many value classes
    • C. Frequency distributions and histograms
    • D. Relative, cumulative and relative cumulative frequency tables
    • E. Shape, center dispersion, skewness kurtosis and outliers by observation only
  • III. CONDENSATION OF DATA
    • A. Measures of central tendency
      • 1. Mean (population)
      • 2. Median
      • 3. Mode
      • 4. Advantages and disadvantages of each
    • B. Measures of dispersion
      • 1. Range
      • 2. Standard deviation (population)
    • C. Distribution of values in a data set
      • 1. General rule (68%, 95%, 99+%)
      • 2. Standardized (z) values
      • 3. Identification of outliers using numerical criteria
    • D. Grouped data
      • 1. Measures of center
      • 2. Measures or dispersion
      • 3. Percentiles
  • STATISTICAL PACKAGE: Use of a statistical package should be integrated with the development of topics presented in I - III. In particular, the following topics should be covered:
    • A. Creating a file
    • B. Defining and editing the structure
    • C. Entering and editing the data
    • D. Adding and deleting variables and cases
    • E. Sorting and grouping data
    • F. Transformation of data
    • G. Statistical procedures
      • 1. Statistics
      • 2. Statistics on subgroups
      • 3. Stem and leaf plots
      • 4. Histograms
      • 5. Frequency distributions
  • IV. INFERENTIAL STATISTICS
    • A. General concepts of probability
      • 1. Relative frequency approach
      • 2. Histograms
    • B. Normal distributions
      • 1. Equivalency of area, proportion and probability
      • 2. Standard normal
      • 3. Transformation of transformation ~ N ( math ) to z~ N( 0,1 )
      • 4. Proportions, probabilities and percentiles
      • 5. Distribution of sample mean distribution ~ N fraction
      • 6. Standard error of the estimate
    • C. Estimation
      • 1. Point estimates(point estimatesand s)
      • 2. Confidence interval estimates of confidence interval estimates
    • D. Hypothesis testing
      • 1. Mean of one population
      • 2. Means of two populations
        • a. t test
        • b. Grouping - independent samples
        • c. Pairing - dependent samples
      • 3. Test for independence of classifications
        • a. distributiondistribution
      • 4. Regression analysis
        • a. Simple linear regression
        • b. Multiple linear regression

STATISTICAL PACKAGE: Topics presented in IV, C and D, should be illustrated and analyzed using statistical procedures in a statistical package. Analysis and interpretation of outputs should be emphasized.


Last Updated: 8/27/13