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Course Description

This course surveys descriptive and inferential statistics with emphasis on practical applications of statistical analysis. The principles of collecting, analyzing, and interpreting data are covered in this course. It examines the role of statistical analysis, terminology, the appropriate use of techniques, and interpretation of statistical findings through the applications and functions of statistical methods.

This graduate course is 6 weeks.

This course has a prerequisite. Please see details in the Prerequisite section below.

PLEASE NOTE:
Attendance and participation are mandatory in all university courses, and specific requirements may differ by course. If attendance requirements are not met, a student may be removed from the course. Please review the Course Attendance Policy in the Catalog for more information.

Topics and Objectives

Introduction to Statistics

  • Evaluate the use of statistics in real-world applications.
  • Describe descriptive and inferential statistical methods and the fundamental elements of statistics.
  • Differentiate between qualitative and quantitative variables.
  • Create visual representations of quantitative and qualitative data.
  • Describe the distribution of quantitative data in terms of shape, center, and spread.

Probability Concepts, Central Tendency, and Variability

  • Calculate central tendency and variability in the context of data sets, accounting for possible effects of extreme data points.
  • Differentiate between discrete, continuous, and conditional probability.
  • Describe how independence and conditional probability are applied in interpreting data.
  • Calculate probabilities of compound events in a uniform probability model by applying the rules of probability.
  • Evaluate the need to calculate expected values for the purpose of solving problems.
  • Describe how the characteristics of standard normal distribution and the Empirical Rule can be used to interpret the significance of standard deviation.

Introduction to Inferential Statistics and Test of Hypothesis

  • Evaluate the steps of hypothesis testing.
  • Determine the distribution of the sample mean and the distribution of the sample.
  • Distinguish an hypothesis regarding a population proportion verses a hypothesis regarding a population mean.
  • Distinguish between the t-test and z-test.
  • Determine statistically whether to accept or reject the null hypothesis.
  • Interpret the results of a hypothesis test.

Chi-square Applications

  • State the steps of the decision rule for a hypothesis regarding the standard deviation.
  • Perform a chi-square test using equal and unequal expected frequencies.
  • Determine normality using a goodness-of-fit test.
  • Interpret relative frequencies in the context of the data.
  • Investigate patterns of association in bivariate data using scatter plots.

Regression and Correlation

  • Use technology to calculate coefficient of correlation and coefficient of determination.
  • Distinguish between correlation and causation.
  • Develop a single linear regression equation.
  • Predict the value of y for a given value of x using a single linear regression equation.
  • Apply analysis of residuals, standard error of estimate, confidence intervals, and prediction.

Review of Topics and Objectives

  • Review course topics and objectives.
  • Apply statistics to real-world scenarios.

Prerequisites

This graduate level course requires proof of completion of a Bachelor's degree. Be prepared to provide documentation during the checkout process.

During the checkout process you will be prompted to provide proof of the requirement(s). If you completed the prerequisite at another institution be prepared to upload an official/unofficial transcript. If you have questions about meeting the prerequisite requirements for this course please contact an enrollment representative at 866-345-1800.

Disclaimers

The University of Phoenix reserves the right to modify courses.

While widely available, not all programs are available in all locations or in both online and on-campus formats. Please check with a University Enrollment Representative

Transferability of credit is at the discretion of the receiving institution. It is the student’s responsibility to confirm whether or not credits earned at University of Phoenix will be accepted by another institution of the student’s choice.

If you have a question please contact us at 866-345-1800.

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Enroll Now - Select a section to enroll in

Section Title
STATISTICS
Type
Instructor Led
Days
T, M
Time
12:00AM to 11:59AM
Dates
Jul 30, 2019 to Sep 09, 2019
Campus
Online Campus
Building
Online Non-Degree
Schedule and Location
Contact Hours
143.8
Location
  • Online Campus
Course Fee(s)
Graduate Tuition Education credit (3 units) $1,620.00 Click here to get more information
Section Fees
Resource Fee $195.00 Mandatory
Credits/Units
3 Credit Hours
Section Title
STATISTICS
Type
Instructor Led
Days
T, M
Time
12:00AM to 11:59AM
Dates
Sep 10, 2019 to Oct 21, 2019
Campus
Online Campus
Building
Online Non-Degree
Schedule and Location
Contact Hours
143.8
Location
  • Online Campus
Course Fee(s)
Graduate Tuition Education credit (3 units) $1,620.00 Click here to get more information
Section Fees
Resource Fee $195.00 Mandatory
Credits/Units
3 Credit Hours
Section Title
STATISTICS
Type
Instructor Led
Days
T, M
Time
12:00AM to 11:59AM
Dates
Oct 22, 2019 to Dec 02, 2019
Campus
Online Campus
Building
Online Non-Degree
Schedule and Location
Contact Hours
143.8
Location
  • Online Campus
Course Fee(s)
Graduate Tuition Education credit (3 units) $1,620.00 Click here to get more information
Section Fees
Resource Fee $195.00 Mandatory
Credits/Units
3 Credit Hours
Section Title
STATISTICS
Type
Instructor Led
Days
T, M
Time
12:00AM to 11:59AM
Dates
Dec 03, 2019 to Jan 27, 2020
Campus
Online Campus
Building
Online Non-Degree
Schedule and Location
Contact Hours
191.7
Location
  • Online Campus
Course Fee(s)
Graduate Tuition Education credit (3 units) $1,620.00 Click here to get more information
Section Fees
Resource Fee $195.00 Mandatory
Credits/Units
3 Credit Hours
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