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Another numerical question is µ1>µ2. µ1 is defined as the sample mean of Hispanic workers salaries and µ2 defined as the sample mean of Caucasian workers salaries. The Hispanic sample population is six workers from the “Wages and Wage Earners Data Set.” Learning Team B needs to consider whether or not the population is normal as the population size is less than 30. This also prohibits use of the Central Limit Theorem until the data set is proven normal. The wage of one worker being much higher than the others means our data will be skewed right and this data may not be a “good” sample. The existence of this outlier means our results will be skewed meaning we should find a better sample to base our results on. More importantly, the existence of an outlier reminds us that the mean is not always a good measure of the “typical” value of X.” (Doane & Seward,
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The team’s null hypotheses or (HO) is that Hispanic pay is greater than or equal to $30,000. The team’s alternative hypothesis or (H1) is that Hispanic pay is less than $30,000. The significance level has been set at .05 or 95%. The z score of .05 is -1.645. If the z-value is less than -1.645 then the team can reject the null hypothesis and accept the alternative hypothesis. If the z-value is greater than -1.645 then the team fails to reject the null hypothesis, meaning Hispanic workers do, in fact, make more than $30,000 a …show more content…
This is because the team performed a one tailed Z-Test to determine with 95% confidence that Hispanic wages were greater than $30,000 per year. This is a one tailed test because the alternate hypothesis is only proven when the Z Value is less than the critical value of $30,000 in this case. With a Z Value of .3163, we find that our Z-Test has yielded a result significantly higher than -1.645, which proves H0, or that Hispanic pay is greater than $30,000 per year. The test also concluded that Hispanic workers make more than Caucasian workers on average. We also gathered data showing the average age of Caucasian workers is higher than that of Hispanic
The team’s null hypotheses or (HO) is that Hispanic pay is greater than or equal to $30,000. The team’s alternative hypothesis or (H1) is that Hispanic pay is less than $30,000. The significance level has been set at .05 or 95%. The z score of .05 is -1.645. If the z-value is less than -1.645 then the team can reject the null hypothesis and accept the alternative hypothesis. If the z-value is greater than -1.645 then the team fails to reject the null hypothesis, meaning Hispanic workers do, in fact, make more than $30,000 a …show more content…
This is because the team performed a one tailed Z-Test to determine with 95% confidence that Hispanic wages were greater than $30,000 per year. This is a one tailed test because the alternate hypothesis is only proven when the Z Value is less than the critical value of $30,000 in this case. With a Z Value of .3163, we find that our Z-Test has yielded a result significantly higher than -1.645, which proves H0, or that Hispanic pay is greater than $30,000 per year. The test also concluded that Hispanic workers make more than Caucasian workers on average. We also gathered data showing the average age of Caucasian workers is higher than that of Hispanic