We would like to determine if the population mean rating of free apps is higher than the population mean rating of paid apps for all apps available on Google Play. State the alternative hypothesis: ["mu1 > mu2", "p1 > p2", "mu sub d > 0"] After carefully exploring the data, we decided to perform a unpooled (Welch’s) t-test. Consider the following two outputs and answer the question below: OUTPUT A ?⎯⎯⎯x¯ s 1. Free 4.78 0.53 2. Paid 4.52 0.13 OUTPUT B ?⎯⎯⎯x¯ s 1. Free 4.78 0.47 2. Paid 3.49 0.38 Which of the provided R outputs has led to the decision to perform the unpooled (Welch’s) t-test? ["output A", "output B", "both"] After evaluating the p-value, we failed to reject H0, the results are not statistically significant. What type of error could we have made if we made one? (type 1, type 2, none)
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We would like to determine if the population mean rating of free apps is higher than the population mean rating of paid apps for all apps available on Google Play.
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State the alternative hypothesis: ["mu1 > mu2", "p1 > p2", "mu sub d > 0"]
-
After carefully exploring the data, we decided to perform a unpooled (Welch’s) t-test. Consider the following two outputs and answer the question below:
OUTPUT A
?⎯⎯⎯x¯
s
1. Free
4.78
0.53
2. Paid
4.52
0.13
OUTPUT B
?⎯⎯⎯x¯
s
1. Free
4.78
0.47
2. Paid
3.49
0.38
Which of the provided R outputs has led to the decision to perform the unpooled (Welch’s) t-test? ["output A", "output B", "both"]
-
After evaluating the p-value, we failed to reject H0, the results are not statistically significant. What type of error could we have made if we made one? (type 1, type 2, none)
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