MATH 1127 Syllabus
Subject Code
MATH
Course Number
1127
Course Title
Introduction to Statistics
Prerequisites
Degree program admission math competency or successful completion of required math learning support courses with a grade of C* or higher
Corequisites
Terms Offered
Offered every semester
Credit Hours
(3-0-3)
Course Description
This course emphasizes the concepts and methods fundamental to utilizing and interpreting commonly used statistics. Topics include descriptive statistics, basic probability, discrete and continuous distributions, sampling distributions, hypothesis testing, chi square tests, and linear regression.
Course Outcomes
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Descriptive Statistics
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Order
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Description
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1
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Draw stem-leaf diagrams and histograms.
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2
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Compute mean, median, mode, and standard deviation.
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Basic Probability
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Order
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Description
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1
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Define events, compound events, and complementary events.
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2
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Compute probabilities for unions, intersections, and complements.
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3
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Compute conditional probabilities.
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Discrete and Continuous Distributions
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Order
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Description
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1
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Demonstrate the difference between discrete and continuous random variables.
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2
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Use probability distributions to compute expected value of a discrete random variable.
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3
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Compute probabilities for binomial distributed random variables.
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4
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Compute expected value and variance of a binomial distributed random variable.
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5
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Compute probabilities for normally distributed random variables.
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6
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Use the normal distribution to estimate probabilities for binomial distributed random variables.
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Sampling Distributions
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Order
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Description
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1
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Use the normal distribution to compute probabilities for samples.
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2
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Determine the sample size required to meet certain requirements for the standard deviation.
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3
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Determine large-sample and small-sample confidence intervals for population means.
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Hypothesis Testing
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Order
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Description
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1
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Explain the meaning of the null and alternative hypothesis.
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2
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Define the meaning of a Type I (α) error.
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3
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Define the meaning of a Type II (ß) error.
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4
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Examine a hypothesis about a population mean using a large sample (normal distribution).
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5
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Examine a hypothesis about a population mean using a small sample (student's t distribution).
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Linear Regression
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Order
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Description
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1
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Match a linear function to best represent the relationship between two variable quantities.
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2
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Compute the correlation coefficient to measure the relationship between two random variables.
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3
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Evaluate the correlation coefficient to measure the relationship between two random variables.
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Chi Square Tests
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Order
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Description
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1
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Compare two or more population proportions and test for differences in populations.
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2
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Examine how well the binomial or normal distribution fit a data set.
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|
Descriptive Statistics
|
|
Order
|
|
Description
|
|
1
|
|
Draw stem-leaf diagrams and histograms.
|
|
2
|
|
Compute mean, median, mode, and standard deviation.
|
|
Basic Probability
|
|
Order
|
|
Description
|
|
1
|
|
Define events, compound events, and complementary events.
|
|
2
|
|
Compute probabilities for unions, intersections, and complements.
|
|
3
|
|
Compute conditional probabilities.
|
|
Discrete and Continuous Distributions
|
|
Order
|
|
Description
|
|
1
|
|
Demonstrate the difference between discrete and continuous random variables.
|
|
2
|
|
Use probability distributions to compute expected value of a discrete random variable.
|
|
3
|
|
Compute probabilities for binomial distributed random variables.
|
|
4
|
|
Compute expected value and variance of a binomial distributed random variable.
|
|
5
|
|
Compute probabilities for normally distributed random variables.
|
|
6
|
|
Use the normal distribution to estimate probabilities for binomial distributed random variables.
|
|
Sampling Distributions
|
|
Order
|
|
Description
|
|
1
|
|
Use the normal distribution to compute probabilities for samples.
|
|
2
|
|
Determine the sample size required to meet certain requirements for the standard deviation.
|
|
3
|
|
Determine large-sample and small-sample confidence intervals for population means.
|
|
Hypothesis Testing
|
|
Order
|
|
Description
|
|
1
|
|
Explain the meaning of the null and alternative hypothesis.
|
|
2
|
|
Define the meaning of a Type I (α) error.
|
|
3
|
|
Define the meaning of a Type II (ß) error.
|
|
4
|
|
Examine a hypothesis about a population mean using a large sample (normal distribution).
|
|
5
|
|
Examine a hypothesis about a population mean using a small sample (student's t distribution).
|
|
Linear Regression
|
|
Order
|
|
Description
|
|
1
|
|
Match a linear function to best represent the relationship between two variable quantities.
|
|
2
|
|
Compute the correlation coefficient to measure the relationship between two random variables.
|
|
3
|
|
Evaluate the correlation coefficient to measure the relationship between two random variables.
|
|
Chi Square Tests
|
|
Order
|
|
Description
|
|
1
|
|
Compare two or more population proportions and test for differences in populations.
|
|
2
|
|
Examine how well the binomial or normal distribution fit a data set.
|