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Apr 29, 2024
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MATH& 146 Introduction to Statistics5 credits
This course covers the organization and graphical representation of data, measures of central tendency and variation, basic probability theory, discrete probability distributions and the binomial formula, the normal distribution, hypothesis testing, confidence intervals, correlation, and linear regression.
This course meets the Quantitative Reasoning general education distribution requirement.
Prerequisites: MATH 98 (recommended) or MATH 99 (or placement into MATH& 146)
Course Outcomes
Upon successful completion of this course the students will be able to:
- Organize and graph data using scatterplots, histograms, and boxplots
- Calculate mean, standard deviation, z-scores, and percentile values
- Solve problems using the basic elements of probability theory, such as sample spaces, the addition rule, and the multiplication rule
- Calculate the mean and standard deviation of a probability distribution
- Calculate expected value
- Calculate probabilities using the binomial probability formula
- Calculate probabilities and find percentile values using the normal distribution and the central limit theorem
- Construct and interpret confidence intervals
- Perform hypothesis tests
- Measure and test for correlation
- Use regression equations to make predictions
General Education Distribution Area Outcomes
Students who successfully complete courses in the Quantitative Reasoning distribution area will be able to:
- Gather, organize, and interpret data using multiple approaches
- Develop and use mathematical models to describe and evaluate physical situations
- Communicate problem-solving strategies and mathematically justify solutions
- Select and utilize appropriate technology to analyze mathematical problems
Total Hours: 50 Theory (Lecture) Hours: 50
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