Question
Question 1: What does it mean when the values in the column of differences (without - with) are negative? Question 2: You wish to test
Question 1:
What does it mean when the values in the column of differences (without - with) are negative?
Question 2:
You wish to test the following claim (HAHA) at a significance level of =0.10. For the context of this problem, d=newold where the first data set represents the hours of stand-by battery life for an old smartphone and the second data set represents the hours of stand-by battery life of a new model of the smartphone. Ho:d=0 Ha:d0 You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain the following sample of data (hours of stand-by time):
old model | new model |
---|---|
68.4 | 26.5 |
59.4 | 38.2 |
50.2 | 25.1 |
54.3 | 22.9 |
62.7 | 73.8 |
57.9 | 90.7 |
46.3 | 40.6 |
62.4 | 65.9 |
What is the test statistic for this sample? (Report answer accurate to three decimal places.) t=____ The p-value is ____ This p-value leads to a decision to...
- reject the null
- accept the null
- fail to reject the null
As such, the final conclusion is that...
- There is sufficient evidence in the sample data to support the claim that on average, the new battery life and old batteyr life for the product are different..
- There is not sufficient evidence in the sample data to support the claim that on average, the new battery life and old batteyr life for the product are different.
Question 3:
You wish to test the following claim (Ha) at a significance level of =0.01. For the context of this problem, d=PostTestPreTest where the first data set represents a pre-test and the second data set represents a post-test. (Each row represents the pre and post test scores for an individual. Be careful when you enter your data and specify what your 1 and 2 are so that the differences are computed correctly.) Ho:d=0 Ha:d0 You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain the following sample of data:
pre-test | post-test |
---|---|
26.8 | 1.2 |
44.9 | 46.4 |
66.3 | 70.4 |
59.9 | 77.5 |
37.2 | 46.2 |
59.9 | 54.7 |
47.2 | 19.3 |
26.1 | 30.6 |
42.2 | 48.6 |
8.1 | -7.3 |
55.1 | 60.1 |
44.5 | 44.8 |
What is the test statistic for this sample? test statistic = _____ (Report answer accurate to 4 decimal places.) What is the p-value for this sample? p-value = ______ (Report answer accurate to 4 decimal places.) The p-value is...
- less than (or equal to)
- greater than
This test statistic leads to a decision to...
- reject the null
- accept the null
- fail to reject the null
As such, the final conclusion is that...
- There is sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is not equal to 0.
- There is not sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is not equal to 0.
- The sample data support the claim that the mean difference of post-test from pre-test is not equal to 0.
- There is not sufficient sample evidence to support the claim that the mean difference of post-test from pre-test is not equal to 0.
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