Two-Group Hypothesis Tests using Excel 2013 T-TEST Command: A Step-by-Step Guide, Exams of MS Microsoft Excel skills

A comprehensive guide on performing two-group hypothesis tests using the Excel 2013 T-TEST command. It covers the purpose of the test, inputs required, and a step-by-step procedure with examples. The document also explains the difference between dependent, matched subjects, population variances unknown but equal, and population variances unknown & unequal types of T-TEST.

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Two group hypothesis tests using Excel 2013 T-TEST command 1
by
Milo Schield
Member: International Statistical Institute
US Rep: International Statistical Literacy Project
Director, W. M. Keck Statistical Literacy Project
Slides and audio at: www.StatLit.org/
pdf/T-TEST-Command-Excel-2013-6up.pdf
Two-Group Hypothesis Tests:
Excel 2013 T-TEST Command
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Download Two-Group Hypothesis Tests using Excel 2013 T-TEST Command: A Step-by-Step Guide and more Exams MS Microsoft Excel skills in PDF only on Docsity!

Two group hypothesis tests using Excel 2013 T-TEST command

by

Milo Schield

Member: International Statistical Institute

US Rep: International Statistical Literacy ProjectDirector, W. M. Keck Statistical Literacy Project

Slides and audio at: www.StatLit.org/

pdf/T-TEST-Command-Excel-2013-6up.pdf

Two-Group Hypothesis Tests:Excel 2013 T-TEST Command

Two group hypothesis tests using Excel 2013 T-TEST command

Excel T-TEST Command

Purpose:

Calculate likelihood (p-value) of getting the observed

difference in two sample means (or more extreme) by chancein random samples – assuming there is no difference in thetwo population means (the Null Hypothesis).

Four Inputs: 1)

Array or range of two samples.

  1. Alpha cutoff.

Tails: 1 (Excel matches Alternate with sample means) or 2.

Type of T-TEST. 1 dependent, matched subjects.2: population variances unknown but equal. [Often true]3: population variances unknown & unequal. [Conservative]

Two group hypothesis tests using Excel 2013 T-TEST command

Approach

Excel’s two-population T-Test command requires that thedata be “stacked” (separated into two groups) by the valueof the predictor. Predictor must be binary.If the binary predictor is the answer to Q1, then

the entire

data set

must be sorted by Q1.

The Excel “Sort” requires that the entire data set be selected before

invoking the sort command. A common mistake is

to sort just a single column rather than the entire dataset.Unfortunately Excel does not have a “stacked” orconditional T-Test. The T-Test command will notautomatically update p-values if data is changed.

Two group hypothesis tests using Excel 2013 T-TEST command

A: From Data tab, select Sort

.

Two group hypothesis tests using Excel 2013 T-TEST command

.

C: Sort Data.

Prepare column headings.

Create headings thatshow what column orquestion is being testedand what column orquestion is used to splitthe data into two groups.Q1 is used as the two-group splitter in thisexample. Any field withbinary data can be used.The vertical bar “|”means “given” soQ2|Q1=1 indicates thevalues of Q2 for whichQ1 equals 1.

Two group hypothesis tests using Excel 2013 T-TEST command

Q1=1 Q1=0.

D: Copy stacked datato separate columns

Two group hypothesis tests using Excel 2013 T-TEST command

T-TEST Command Procedure

Given Separated Data

1:

From Tool Menu, select “Data Analysis”.

2:

From Data Analysis window, select “t-test: Two-sample with unequal variances”.

3:

From associated window, enter inputs and outputs.

Obtain results of t-test.

Two group hypothesis tests using Excel 2013 T-TEST command

1) From the Data ribbon

select Data Analysis

Two group hypothesis tests using Excel 2013 T-TEST command

3) Enter Input & Output:

Q2 by Q

Two group hypothesis tests using Excel 2013 T-TEST command

4) Excel-Generated Results:

Q2 by Q

Difference in Q2 proportions by Q1 in not statistically significant

Technical: Fail to reject the null hypothesis for Q2 by Q1.

Two group hypothesis tests using Excel 2013 T-TEST command

4) Excel-Generated Results:

Q7 by Q

Difference in Q7 means by Q1 IS statistically significant (1 tail)

Technical: Reject the null hypothesis for Q7 by Q1 (1 tail)

Two group hypothesis tests using Excel 2013 T-TEST command

3) Enter Input and Output:

Q8 by Q

Two group hypothesis tests using Excel 2013 T-TEST command

Summary

In a one-tailed test, T-TEST always tests whether thepositive difference between the larger sample statisticand the smaller is statistically-significant.“Reject the null hypothesis” and “Failure to reject thenull hypothesis” are technical conclusions.“A difference IS [or IS NOT] statistically significant”is a less-technical conclusion.Use the less-technical expressions for everydaycommunication.