MATH 2311

Elementary Statistical Methods

0.5 credits · Undergraduate

Winter 2026

Topics

of hypothesis, simple linear regression and correlation, multiple regression, analysis of variance
(ANOVA), analysis of categorical data, topics in experimental design, and basic nonparametric statistics
right to add or delete sections to the list
Successful students of this course
give interpretations
Analyze and develop the integrity, meaning, and mechanics of the confidence interval reasoning
probability
Analyze and develop the integrity, meaning, and mechanics of the hypothesis testing reasoning
Perform hypothesis testing regarding the population mean, variance, and proportion
Use appropriate statistical tests to compare means, variances, or proportions from different
populations
Linear regression with one or more variables
Analysis of variance methods
Goodness of fit tests
Selected topics such as: non-parametric methods, experimental designs, analysis of covariances
Use of statistical software(s)
Fridays 5:30 PM - 6:30 PM in RB-1022
get help to finish your assignments

Statistics, 13th Edition by James T. McClave and Terry Sincich Paper copies of this

Winter 2020

of hypothesis, simple linear regression and correlation, multiple regression, analysis of variance
(ANOVA), analysis of categorical data, topics in experimental design, and basic nonparametric statistics
to add or delete sections to the list
Successful students of this course
give interpretations
Analyze and develop the integrity, meaning, and mechanics of the confidence interval reasoning
probability
Analyze and develop the integrity, meaning, and mechanics of the hypothesis testing reasoning
Perform hypothesis testing regarding the population mean, variance, and proportion
Use appropriate statistical tests to compare means, variances, or proportions from different
populations
Linear regression with one or more variables
Analysis of variance methods
Goodness of fit tests
Selected topics such as: non-parametric methods, experimental designs, analysis of covariances
Use of statistical software(s)
get help to finish your assignments. If there is no student showing up during the first 5 minutes, this Q’s

Statistics, 13th Edition by James T. McClave and Terry Sincich. Optional: Student’s Solution Manual. Prerequisite: MATH-2310 Credit Weight: 0.5 (Not recognized as a mathematics credit for any Mathematics Major.)

Winter 2015

variance (ANOVA), analysis of categorical data, topics in experimental design, and basic
and even get help to finish your assignments. If there is no student showing up during the first

Statistics, 12th Edition by James T. McClave and Terry Sincich. Optional: Student’s Solution Manual. Prerequisite: MATH-2310 Credit Weight: 0.5 (Not recognized as a mathematics credit for Mathematics or Computer Science majors.)

Sources