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Confidence Intervals and Chi Square For questions 3 and 4 below, be sure to list the null and alternate hypothesis statements. Use .05 for your significance level in making your decisions. For full credit, you need to also show the statistical outcomes - either the Excel test result or the calculations you performed. 1 Using our sample data, construct a 95% confidence interval for the population's mean salary for each gender. Interpret the results. How do they compare with the findings in the week 2 one sample t-test outcomes (Question 1)? Mean St error t value Low to High Males Females <Reminder: standard error is the sample standard deviation divided by the square root of the sample size.> Interpretation: 2 Using our sample data, construct a 95% confidence interval for the mean salary difference between the genders in the population. How does this compare to the findings in week 2, question 2? Difference St Err. T value Low to High Yes/No Can the means be equal? Why? How does this compare to the week 2, question 2 result (2 sampe t-test)? a. Why is using a two sample tool (t-test, confidence interval) a better choice than using 2 one-sample techniques when comparing two samples? 3 We found last week that the degrees compa values within the population. do not impact compa rates. This does not mean that degrees are distributed evenly across the grades and genders. Do males and females have athe same distribution of degrees by grade? (Note: while technically the sample size might not be large enough to perform this test, ignore this limitation for this exercise.) What are the hypothesis statements: Ho: Ha: Note: You can either use the Excel Chi-related functions or do the calculations manually. Data input tables - graduate degrees by gender and grade level OBSERVED A B C D E F Total Do manual calculations per cell here (if desired) M Grad A B C D E F Fem Grad M Grad Male Und Fem Grad Female Und Male Und Female Und Sum = EXPECTED M Grad For this exercise - ignore the requirement for a correction Fem Grad for expected values less than 5. Male Und Female Und Interpretation: What is the value of the chi square statistic: What is the p-value associated with this value: Is the p-value <0.05? Do you reject or not reject the null hypothesis: If you rejected the null, what is the Cramer's V correlation: What does this correlation mean? What does this decision mean for our equal pay question: 4 Based on our sample data, can we conclude that males and females are distributed across grades in a similar pattern within the population? What are the hypothesis statements: Ho: Ha: Do manual calculations per cell here (if desired) A B C D E F A B C D E F OBS COUNT - m M OBS COUNT - f F Sum = EXPECTED What is the value of the chi square statistic: What is the p-value associated with this value: Is the p-value <0.05? Do you reject or not reject the null hypothesis: If you rejected the null, what is the Phi correlation: What does this correlation mean? What does this decision mean for our equal pay question: 5. How do you interpret these results in light of our question about equal pay for equal work?
A large retail corporation plans to sample sales receipts of its meat department to estimate the average size (in dollars) of a customer purchase. Previous analysis suggest that the standard deviation of the purchase amount is approximately $50.72..
A random sample of stipends of teaching assistants in economics is listed below. Is there sufficient evidence at the alpha=.05 level to conclude that the average stipend different from $15,000? The data is listed below:
Assume that the weights of coconuts are normally distributed with a mean weight of 17.6 pounds and a standard deviation of 1.2 pounds.
Based on the boxplots in part (a), which of the two groups, students or teachers, tends to have watch times that are closer to the true time? explain you choice.
Conduct a hypothesis test to test that the population mean for population A is no greater than the population mean for B. Use the 0.08 significance level.
Iif the sample consits of 16 scores, is the sample mean sufficient to conclude that the treatment has a significant effect? use a two tailed test with .05.
How would you interpret the findings of a correlation study that reported a linear correlation coefficient of +0.3?
Could you explain the Pearson or product-moment correlation? If we were to use a partial correlation, would you want to look at the relationship between two variables while removing the effect of one or two other variables?
Find the probability that a random selected score is between 150 and 157. If a sample of size n = 100 is randomly selected, find the probability that the sample mean will be between 150 and 157.
If Larry gets a 70 on a physics test where the mean is 65 and the standard deviation is 5.8, where does he stand in relation to his classmates?
What about these descriptive statistics makes you wary or uncomfortable? In other words, if you were a real estate agent, would you go around spouting the answers that you gave above? Explain.
At the .01 significance level, can we conclude that there is more variation?
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