# Course Description

Schoolcraft is excited to offer traditional credit face-to-face, hybrid, online, and remote classes. We are committed to providing students a safe experience based on recent COVID-19 concerns.

Please see the COVID-19 web page to learn more. Keep checking the schedule for additions on our New, Added, and Late Starting Courses web page.

# Mathematics - MATH 122

## Elementary Statistics

### Course Description

This course includes an introduction to statistics, statistical descriptions, frequency distributions, possibilities and probabilities, probability distributions, sampling and sampling distributions, testing hypotheses based on measurements, count data, paired data and use of nonparametric tests.

### Prerequisites

(A requirement that must be completed before taking this course.)

• MATH 113 with a minimum grade of 2.0 or a minimum score of 23 ACT-Math, 29 SAT-Math, 63 CPT-College-Level Math or 265 NGA-Quantitative Reasoning, Algebra and Statistics.

### Course Competencies

Upon successful completion of the course, the student should be able to:

• Create visual presentations using sample data both by hand and by using statistical software, including a tabular frequency distribution, stem-and-leaf plot, histogram, frequency polygon and pie chart.
• Compute descriptive statistics both by using an algorithm and by using statistical software, including the mean, median, mode, fractiles, range, variance and standard deviation.
• Determine whether a given sampling method yields a random sample, simple random sample, stratified sample, etc.
• Use a random number generator to select a random sample from a given population.
• Determine the number of possible outcomes of an event with the aid of the addition, multiplication, complement, factorial and other rules.
• Calculate probability of an event by using the classical approach.
• Estimate the probability of an event by using the relative frequency approach.
• Determine the conditional probability of one event given another event by using the defining formula for conditional probability.
• Determine probabilities for various discrete distributions (including the uniform, binomial and hypergeometric) by all of the following means: a formula, a table and statistical software.
• Determine probabilities for various continuous distributions (including the Gaussian normal and Student's t) by using a formula and either a table or statistical software.
• Interpret probabilities of a discrete random variable as the area of bars in its histogram.
• Interpret probabilities of a continuous random variable as the area under the graph of its density function.
• Solve practical problems involving probability distributions.
• Determine the mean (expected) value and the standard deviation of a discrete random variable using its probability distribution.
• Determine whether two events are independent of one another by using their probabilities.
• Determine a confidence interval for a population mean, based on a random sample and the normal or t-distribution (as appropriate), both by using a formula and table and by using statistical software.
• Test a hypothesis regarding one, two or several population means, based on random sample(s) and the normal, t- or ANOVA distribution (as appropriate), both by using a formula and table and by using statistical software.
• Determine a confidence interval for a population proportion, based on a random sample and the normal distribution, both by using a formula and table and by using statistical software.
• Test a hypothesis regarding one, two or several population proportions, based on a random sample(s) and the normal, t or chi-squared distribution (as appropriate), both by using a formula and table and by using statistical software.
• Determine Pearson's linear correlation coefficient r for a sample of bivariate data, both by using a formula and by using statistical software.
• Determine the least-squares linear regression fit to a sample bivariate data.
• Test a hypothesis regarding the linear correlation between two variables, based on a random sample and on critical values of the r-distribution, both with the aid of a table and the aid of statistical software.
• Test a hypothesis regarding one or two population medians or a population proportion, based on a random sample(s) and the sign test.
• Test a hypothesis regarding the linear correlation between two variables, based on a random sample and Spearman's rank-correlation test.
• Investigate sampling distributions of statistics.

### Course Schedule

CourseSectionCourse TitleLocationCredit HoursInstructorsSeats Available ⁄Capacity ⁄WaitlistStatusFeeDays-Time-Room

Winter; 2021; MATHEMATICS; No of Weeks : 12; Begins : 01/11/2021

122112724Elem StatisticONL4Stetson B3/31/0Open\$12.00
122112784Elem StatisticONL4Choraszewski L4/31/9Closed\$12.00

Winter; 2021; MATHEMATICS; No of Weeks : 12; Begins : 02/02/2021

122112787Elem StatisticONL4Stetson B0/31/0Closed\$12.00
122112789Elem StatisticONL4Stetson B0/31/0Closed\$12.00

Winter; 2021; MATHEMATICS; No of Weeks : 15; Begins : 01/11/2021

122112734Elem StatisticONL4Stetson B3/31/0Open\$12.00
122112744Elem StatisticONL4Stetson B3/31/0Open\$12.00
122113013Elem StatisticRMT4Jankoviak Anderson K0/24/0Closed\$12.00T R  12:00 PM-01:54 PM WEBWEB
122113017Elem StatisticRMT4Jankoviak Anderson K2/24/0Open\$12.00M W  01:00 PM-02:54 PM WEBWEB
122113021Elem StatisticRMT4Jankoviak Anderson K4/24/0Open\$12.00T R  08:00 AM-09:54 AM WEBWEB
122113035Elem StatisticRMT4Gerich R2/24/1Closed\$12.00T R  10:00 AM-11:54 AM WEBWEB
122113052Elem StatisticRMT4Weyand G5/24/0Open\$12.00M W  06:00 PM-07:54 PM WEBWEB
122113075Elem StatisticRMT4Weyand G4/24/0Open\$12.00T R  06:00 PM-07:54 PM WEBWEB
122113130Elem StatisticRMT4Jankoviak Anderson K2/24/0Open\$12.00M W  09:00 AM-10:54 AM WEBWEB
122216122Elem StatisticRMT4Gerich R1/24/0Open\$12.00T R  12:00 PM-01:54 PM WEBWEB

Key: Day of the Week

• T = Tuesday
• R = Thursday
• S = Saturday
• X = Sunday

Key: Class Location