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Hypothesis Testing - Gender and Productivity by Machine Weight

A researcher wants to determine how productive males and females are when working with machines of varying weights. His first hypothesis is that there is no difference between males and females in the number of teddy bears they can produce in a typical 8-hour shift. His second hypothesis is that the weight of machinery used makes no difference on productivity. His third hypothesis is that there is no interaction between gender and weight of a processing machine.

Assume that he has controlled all other variables that could interact with the two designated independent variables. Among these variables are age, working experience, factory conditions, and type of product. In other words, all teddy bears are the same size. Further assume that the 30 participants have been chosen at random after age and experience were controlled.

Below are the data that you should input to Excel's two-way ANOVA with replication program.

The Toy Factory Problem
Light Wt Mid Wt Heavy Wt
male 20 43 57
male 21 42 62
male 16 39 60
male 19 38 65
male 17 40 73
female 55 38 21
female 64 39 19
female 62 40 24
female 71 37 14
female 54 41 15

(a) (5) Attach your Excel printout.
b) (5) Analyze the Excel report and discuss the findings. What would you do if you were a manager at that toy factory?

Solution Summary

Word and Excel documents attached perform an ANOVA on a given dataset to determine whether gender has any effect on the number of teddy bears workers can product in a shift on variously-weighted machines.