Apr 19, 2024  
2018-2019 Course Catalog 
    
2018-2019 Course Catalog [ARCHIVED CATALOG]

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MAT 160 - Statistical Business Appl.

Credits: 2
Lecture Hours: 2
Lab Hours: 0
Practicum Hours: 0
Work Experience: 0
Course Type: Open
This is the second course in the statistics sequence. Course content includes application and interpretation of probability and statistics as applied to business situations by using sampling, confidence intervals, control charges, simple linear regression analysis, multiple regression analysis, correlation analysis, data analysis, time series analysis, hypothesis testing and computer analysis.
Prerequisite:  MAT 157  with a C- or better
Competencies
  1. Discuss statistical processes
    1. Compare and contrast descriptive and inferential statistics
    2. State the elements of statistical problems
    3. Discuss the role of statistics in managerial decision-making
  2. Discuss sampling distributions
    1. State properties
    2. Calculate representative values
    3. Compare the relationship between sample size and a sampling distribution
  3. Discuss estimation and a test of hypothesis
    1. Calculate large-sample estimation of a population mean
    2. Calculate necessary sample size
    3. Write appropriate hypotheses
    4. Calculate and interpret p-values
    5. Distinguish between Type I and Type II errors
    6. Interpret results of hypothesis tests
  4. Discuss quality control charts
    1. Calculate appropriate values
    2. Draw appropriate charts
    3. Analyze and interpret results
  5. Discuss simple linear regression
    1. Define a first-order model
    2. Calculate, using least squares method
    3. State assumptions
    4. Calculate an estimate for the population variance
    5. Assess the usefulness of the model
    6. Calculate and interpret coefficient of determination
    7. Estimate and predict, using the model
    8. Perform hypothesis tests
    9. Calculate, using computer spreadsheets
  6. Discuss multiple regression
    1. Identify the model assumptions
    2. Calculate the model, using the method of least squares
    3. Estimate variance of population
    4. Estimate and test hypothesis
    5. Test the usefulness of the model
    6. Estimate and predict, using the model
    7. Relate to business world
    8. Calculate, using computer spreadsheet
    9. Perform residual analyses
    10. Identify pitfalls
  7. Discuss qualitative independent variables
    1. Use appropriate terminology
    2. Write a model



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