tutorial mean difference
DESCRIPTION
Statistical Analytics (Comparing means test) One-sample T-test, Indepedent samples T-test, ANOVA, Cross-tab chi-square testTRANSCRIPT
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Tutorial: Statistical Tests for Mean Differences
Number Analytics
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Statistical Tests for Differences
Choose the correct statistic test to compare means
Area of Application
Level Scaling Subgroups Test Example
Hypotheses about
frequency Nominal All Chi-square
Do customer industry types differ by company size ?
Hypotheses about means
Metric (Interval
or ratio)
One One Sample
T-test Is the purchase frequency
different from 1.5?
Two Independent
Samples T-test
Is the purchase frequency greater for email promotion
responders than that for non-responders?
Three or more One-way ANOVA
Is the purchase frequency different by company size?
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One Sample T-test
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One Sample T-test
You can choose your own file by uploading it to the cloud.
Is the overall rating significantly different than 4?
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One Sample T-test
Then manually enter the test value and choose the sided test.
First select the test variable in your data file
3 STEPS! Easy to apply!
Now click on ‘Run’!
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One Sample t-test
Conclusion: Rating is not different from 4 on average.
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Independent Samples T-test
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Independent Samples T-test
Now we’re interested to know whether
the rating for female group is
significantly different from rating for
male group.
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Independent Samples T-test
Choose the grouping variable
Select the test variable
Let’s run results!
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Independent Samples T-test
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ANOVA
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ANOVA
How about the rating among different ethnical groups?
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ANOVA
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ANOVA
P value 0.32 (>0.05) Conclusion: Rating is indifferent
across ethnicity.
P Value: Exact Probability of getting a computed test statistic that is due to chance. The smaller the p value, the smaller the probability that the observed result occurred by chance
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Cross-tab (Chi-square test)
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Cross-tab (Chi-square test)
• Cross-tab is a frequency table of two
or three variables
• Used to examine association between
two or 3 variables (usually 2)
• H0: there is a relation between variable X
and variable Y
• Variables take a limited number of
values, for example:
Consumers: gender, ethnicity
Business: industry, company size
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Cross-tab (Chi-square test)
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Cross-tab (Chi-square test)
P value greater than 0.05, reject H0. Conclusion: There is no relation between
gender and ethnicity