Apr 25, 2024  
Catalog 2023-2024 
    
Catalog 2023-2024

STAT 243Z Elementary Statistics 1


Lecture Hours: 4
Credits: 4

A first course in statistics focusing on the interpretation and communication of statistical concepts.  Introduces exploratory data analysis, descriptive statistics, sampling methods and distributions, point and interval estimates, hypothesis tests for means and proportions of one population, and elements of probability and correlation. Technology will be used when appropriate.

Prerequisite: Placement into WR 115  (or higher), or completion of WR 090  (or higher); and placement into MTH 243 (or higher), or completion of MTH 105Z  (or higher) or equivalent course as determined by instructor; or consent of instructor. (All prerequisite courses must be completed with a grade of C or better.)
Student Learning Outcomes:
Common Course Number Outcomes:

  1. Critically read, interpret, report, and communicate the results of a statistical study along with evaluating assumptions, potential for bias, scope, and limitations of statistical inference. (a) Students will classify study designs and variable types and identify methods of summary and analysis. 
  2. Produce and interpret summaries of numerical and categorical data as well as appropriate graphical and/or tabular representations. (a) Students will be able to identify patterns and striking deviations from patterns in data. (b) Students will be able to identify associations between variables for bivariate data. (c) Students will apply technology to calculate statistical summaries and produce graphical representations. 
  3. Use the distribution of sample statistics to quantify uncertainty and apply the basic concepts of probability into statistical arguments. (a) Students will compute and interpret point and interval estimates.
  4. Identify, conduct, and interpret appropriate parametric hypothesis tests.
  5. Assess relationships in quantitative bivariate data.

 

Statewide General Education Outcomes:

  • Use appropriate mathematics to solve problems.
  • Recognize which mathematical concepts are applicable to a scenario, apply appropriate mathematics and technology in its analysis, and then accurately interpret, validate and communicate the results.


Content Outline
  • Introduction to Statistics
    • The nature of data
    • Uses and abuses of statistics
    • Design of experiments
  • Describing, Exploring, and Comparing Data
    • Summarizing data and pictures of data
    • Measures of central tendency, variation, and position
    • Exploratory data analysis
  • Probability Distributions
    • Random variables
    • Binomial probability distribution
    • Mean and standard deviation of the binomial distribution
  • Normal Probability Distributions
    • The standard normal distribution
    • Non-standard normal distributions: finding probabilities and scores
    • The Central Limit Theorem
    • Normal approximation to binomial (optional)
  • Estimates and Sample Sizes
    • Estimating a population mean: large and small samples
    • Estimating a population proportion
    • Estimating a population standard deviation or variance (optional)
    • Determining sample size (optional)
  • Hypothesis Testing
    • Testing a claim about a mean: large and small samples
    • Testing a claim about a population proportion
    • Testing a claim about a population standard deviation or variance (optional)
    • Type I and II error in hypothesis test conclusions
  • Linear Regression and Correlation
    • Use technology to construct the regression model and compute the correlation coefficient.
    • The meaning of correlation
  • Counting and Probability (optional as time allows)
    • Fundamentals of probability and addition rule
    • Multiplication rule
    • Simulations