A professor at the University of New Hampshire was interested in evaluating the effect of the unemployment rate on the incarceration rate. Using data from 50 states and the District of Columbia (n = 51), the
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A professor at the University of New Hampshire was interested in evaluating the effect of the unemployment rate on the incarceration rate. Using data from 50 states and the District of Columbia (n = 51), the researcher computed the Pearson’s
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Incarceration |
Unemployment |
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Incarceration |
Pearson Correlation |
1 |
.209 |
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Sig. (2-tailed) |
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.142 |
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N |
51 |
51 |
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Unemployment |
Pearson Correlation |
.209 |
1 |
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Sig. (2-tailed) |
.142 |
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N |
51 |
51 |
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Question |
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What is the sample? |
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What is the dependent variable? |
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What is the independent variable? |
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- A professor at the University of New Hampshire was interested in evaluating the effect of the unemployment rate on the incarceration rate. Using data from 50 states and the District of Columbia (n = 51), the researcher computed the Pearson’s correlation coefficient between the two variables. The results are presented below. Correlations Incarceration Unemployment Incarceration Pearson Correlation 1 .209 Sig. (2-tailed) .142 N 51 51 Unemployment Pearson Correlation .209 1 Sig. (2-tailed) .142 N 51 51 Using an alpha level of 0.05 and the four steps of the hypothesis testing process, test the research hypotheses that unemployment increases incarceration. Step 3 Step 4 Based on your decision to step 4 what type of error might you be making?For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of five types of automobile, the linear correlation coefficient is found and the P-value is 0.033. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is nothing%, which is ▼ high, low, so there ▼ is not is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.The authors of this study report a Pearson correlation coefficient estimate of r = 0.23 with a p-value of <0.01. Interpret.
- . A professor at the University of New Hampshire was interested in evaluating the effect of the unemployment rate on the incarceration rate. Using data from 50 states and the District of Columbia (n = 51), the researcher computed the Pearson’s correlation coefficient between the two variables. The results are presented below. Correlations Incarceration Unemployment Incarceration Pearson Correlation 1 .209 Sig. (2-tailed) .142 N 51 51 Unemployment Pearson Correlation .209 1 Sig. (2-tailed) .142 N 51 51 Based on the result of the hypotheses test above: If states want to reduce the number of individuals incarcerated in their state should they put money into programs to reduce unemployment?calculate Spearman’s correlation coefficient for the data1. Calculate the correlation coefficient. 2. What do these data indicate about the height of the initial drop of a roller coaster and the duration of the ride? O A. Generally, rides on coasters with a greater initial drop tend to last somewhat shorter, because the correlation indicates a moderate association.O B. Generally, rides on coasters with a greater initial drop tend to last longer, because the correlation indicates a strong association.O C. Generally, rides on qpasters with a greater initial drop tend to last somewhat longer, because the correlation indicates a moderate association.O D. Generally, rides on coasters with a greater initial drop tend to last somewhat longer, because the correlation indicates a weak association.