STA2023 - Introduction to Statistics

Topical Outline with Specific Course Objectives

  1. Descriptive Statistics
    1. Calculate and interpret the various descriptive measures for centrality and dispersion.
    2. Determine potential outliers of data sets and understand how they affect the various numerical measures.
    3. Analyze and/or compare different sets of data using graphs, charts, tables, and numerical measures, and write about them in clear and precise sentences using statistical vocabulary.
    4. Demonstrate an understanding of the different types of distributions.
    5. Organize and display data by means of various tables, charts, and graphs.
    6. Define and use the basic terminology of statistics.
  2. Simple Linear Regression and Correlation
    1. Find and interpret the sample correlation coefficient (r) to determine the strength and direction of the linear relationship between predictor and response variables.
    2. Use scatter plots to determine if outliers are present and if data can be represented by a simple linear regression model.
    3. Find the simple linear regression model and be able to interpret the slope and y-intercept.
    4. Use r-squared to determine if a simple linear regression model is a strong predictor.
    5. Predict values of “y” using the simple linear regression model
  3. Normal Probability Distribution
    1. Calculate and interpret a z-score as a measure of relative standing and use it as it applies to the normal model.
    2. Understand the Normal Probability Distribution and be able to determine appropriate areas under a normal curve.
    3. Use the 68-95-99.7 Rule (Empirical Rule) to find probabilities on an approximately normal or bell-shaped distribution.
    4. Use a histogram or normal probability plot, determine if a sample comes from a normally distributed population.
  4. Fundamentals of Probability
    1. Understand and apply basic rules of probability.
    2. Understand and apply the Binomial Probability Distribution.
    3. Identify the random variable involved in a statistical problem and distinguish between: categorical vs quantitative, discrete vs continuous, and binomial vs normal.
  5. Inferential Statistics
    1. Demonstrate at least a rudimentary understanding of basic sample and experimental design (i.e. randomness, bias, etc. ).
    2. Understand and apply sampling distribution models for sample proportions and sample means
    3. Understand and apply the Central Limit Theorem.
    4. Estimate means and proportions using confidence intervals for one and two populations.
    5. Be able to perform hypothesis tests on means and proportions for one and two populations.
    6. Determine and interpret p-values.
  6. Demonstrate competency in the use of technology, including graphing calculator and/or statistical computer software as it applies to topics I – V.

Department Policies

  • Graphing Calculator Required
  • Comprehensive Final
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