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Summary CLC056 Analyzing Contract Costs lesson 12 - Using Regression Analysis | 2022 LATEST UPDATE $10.49   Add to cart

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Summary CLC056 Analyzing Contract Costs lesson 12 - Using Regression Analysis | 2022 LATEST UPDATE

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CLC056 Analyzing Contract Costs lesson 12 - Using Regression Analysis | 2022 LATEST UPDATE

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  • March 16, 2022
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CLC056 Analyzing Contract Costs
lesson 12 - Using Regression Analysis RESOURCES I PR INT I HELP

Introduction

Welcome to Using Regression Analysis!

You might be wondering, "How will the
information in this lesson help me in my job as
a contract specialist?"

As a contract specialist, you may need to use
regression analysis in developing cost
estimating relationships and other analyses
based on a straight- line relationship even
when the data points do not fall on a straight
line.

This lesson will provide information on simple
regression (2-variable linear regression) in
which a single independent variable (X) is used
to predict the value of a single dependent
variable (Y).




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,Long Description

Binder with spine text that reads: Using Regression Analysis. A sticky note is on the front of the binder
that reads: Using regression analysis is an important part of your job as a contract specialist.

,CLC056 Analyzing Contract Costs
lesson 12 - Using Regression Analysis RESOURCES I PRI NT I HELP

Obj ectives

At the end of this lesson, you will be able to:

• Define regression analysis
• I dentify the di fferent regression analysis
methods
• Identify contract pricing situations where
simple regression analysis should be
considered
• Identify the steps for using simple regression
analysis




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, CLC056 Analyzing Contract Costs
lesson 12 - Using Regression Analysis RESOURCES 1 PRI NT 1 HELP


Overview - What Is Regression Analysis?

Regression analysis is a statistical technique used
to establish the relationship of an independent
variable, such as thrust or square footage, and
one or more dependen t variables, such as the
cost of aircra ft engines or housing.

Essentially, regression analysis attempts to
measure the degree of correlation between the
dependent and independent variables. This
analysis establishes the independent variables'
predictive value.




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