Feb 22, 2024  
2017-2018 Course Catalog 
2017-2018 Course Catalog [ARCHIVED CATALOG]

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MATH 1025 - Statistics

Credits: 4
Hours/Week: Lecture 4Lab None
Course Description: This course is an algebra-based statistics course that introduces the basic concepts involved in collecting, analyzing, and interpreting data. Topics include graphs, frequency distributions, measures of central tendency and variation, probability, probability distributions, expected value, sampling distributions, normal distribution, confidence intervals, hypothesis testing for one and two population means and proportions, chi square, linear regression, and correlation. This course includes analysis and interpretation of data using the Minitab software package and using the TI-83/TI-84 calculator. Students are required to have a TI-83 or a TI-84 calculator. MnTC Goal 4
MnTC Goals
4 Mathematics/Logical Reasoning

Prerequisite(s): Assessment score placement in MATH 1025 or higher, or MATH 0060   with a grade of C or higher, or MATH 0070  with a grade of C or higher, or MATH 1030  or above with a grade of C or higher.
Corequisite(s): None
Recommendation: Assessment score placement in RDNG 1000  or completion of RDNG 0900  or RDNG 0950  with a grade of C or higher.

Major Content
  1. Organization of Data
    1. tables and graphs
    2. frequency distributions
  2. Linear Regression and Correlation
  3. Central Tendency
  4. Variation
  5. Probability
  6. Probability Distributions
  7. Sampling Distributions
  8. Confidence Intervals
  9. Hypothesis Testing
  10. Chi-Square

Learning Outcomes
At the end of this course students will be able to:

  1. Demonstrate critical and logical reasoning when solving problems.
  2. Analyze and interpret data using technology, including the TI-83 calculator and Minitab software.
  3. Communicate clearly a problem¿s solution and its explanation for the intended audience in terms of the problem posed.
  4. Organize and interpret data using graphs, frequency distributions, and measures of central tendency.
  5. Calculate probabilities of simple and compound events.
  6. Analyze probability distributions, including binomial, normal, chi-square, and students t-distributions.
  7. Apply statistical methods to normal distributions.
  8. Compute and interpret confidence intervals for one and two population means and proportions.
  9. Test hypotheses for one and two population means and proportions.
  10. Perform chi-square claims tests and tests of independence.
  11. Apply simple linear regression and correlation techniques.

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