What is a hypothesis test?

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(Hypotheses)

What is a hypothesis test?

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Why do we need to use them to make decisions about relating sample results to the population; why can’t we just make our decisions by the sample value?

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(Variation)

Variation exists in virtually all parts of our lives. We often see variation in results in what we spend (utility costs each month, food costs, business supplies, etc.).  Consider the measures and data you use (in either your personal or job activities).

 

When are differences (between one time period and another, between different production lines, etc.) between average or actual results important?

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How can you or your department decide whether or not the observed differences over time are important?

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How could using a mean difference test help?

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(ANOVA)

In many ways, comparing multiple sample means is simply an extension of what we covered last week.  Just as we had 3 versions of the t-test (1 sample, 2 sample (with and without equal variance), and paired; we have several versions of ANOVA – single factor, factorial (called 2-factor with replication in Excel), and within-subjects (2-factor without replication in Excel).

 

What examples (professional, personal, social) can you provide on when we might use each type?

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What would be the appropriate hypotheses statements for each example? 

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(Effect Size)

Several statistical tests have a way to measure effect size.

 

What is this, and when might you want to use it in looking at results from these tests on job related data?

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(Confidence Intervals)

Many people do not “like” or “trust” single point estimates for things they need measured.

 

Looking back at the data examples you have provided in the previous discussion questions on this issue, how might adding confidence intervals help managers accept the results better?  Why?
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Ask a manager in your organization if they would prefer a single point estimate or a range for important measures, and why?  Please share what they say.
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(Chi-Square Tests)
Chi
-square tests are great to show if distributions differ or if two variables interact in producing outcomes.

 

What are some examples of variables that you might want to check using the chi-square tests?

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What would these results tell you?
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(Correlation)

What results in your departments seem to be correlated or related (either causal or not) to other activities?

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How could you verify this?

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What are the managerial implications of a correlation between these variables?

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(Regression)
At times we can generate a regression equation to explain outcomes.  For example, an employee’s salary can often be explained by their pay grade, appraisal rating, education level, etc. 

 

What variables might explain or predict an outcome in your department or life? 

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If you generated a regression equation, how would you interpret it and the residuals from it?

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