Number 24 24. Crickets and Temperature One classic application of correlation involves the associa-tion between the temperature and the number of times a cricket chirps in a minute. Listedbelow are the numbers of chirps in 1 min and the corresponding temperatures in °F (basedon data from The Song of Insects by George W. Pierce, Harvard University Press). Is there suf-ficient evidence to conclude that there is a linear correlation between the number of chirps in1 min and the temperature?Chirps in 1 min8821188110486412001032960900Temperature (°F)69.793.384.376.388.682.671.679.6 Testing fora Linear Correlation.find the value of the linear correlation coefficient r. Also find the P-value or the criticalvalues of r from Table A-6 using a = 0.05. Determine whether there is sufficient evidenceto support a claim of a linear correlation between the two variables. (Save your workbecause the same data sets will be used in Section 10-3 exercises.)In Exercises 13-28, construct a scatterplot, and

Name: Number 24 24. Crickets and Temperature One classic application of corr
Uploaded: 2024-03-05T11:52:21.000Z
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Description: Number 24 24. Crickets and Temperature One classic application of correlation involves the associa-tion between the temperature and the number of times a cricket chirps in a minute. Listedbelow are the numbers of chirps in 1 min and the corresponding

Solution: The data on the numbers of chirps in 1 minute and the corresponding temperatures in °F is given. A scatterplot of the given data is required. It can be easily done using MS-Excel. For that, enter the given data in excel. Select the data of the numbers of chirps in 1 minute and temperatures. On the Insert tab, in the Charts group, click the Scatter symbol. Click Scatter. The value of linear correlation coefficient (r) is required. It can also be found using MS-Excel. In any empty cell of this excel sheet, type =CORREL(A2:A9,B2:B9) and hit enter. It gives 0.873679. Thus, the linear correlation coefficient (r) = 0.873679. It is asked to test the claim of a linear correlation between the number of chirps in 1 minute and temperature. The null and alternative hypotheses are as follows: Null hypothesis (H0): There is no correlation between the two variables. Alternative hypothesis (H1): The given two variables are correlated with each other. The level of significance (α) is given to be 0.05. Critical value: It can be found using the Pearson Correlation table. Here, number of data pairs: n = 8 Thus, critical value = 0.632 Decision Rule: If |r| > critical value from the Pearson table, then reject the null hypothesis. |r| = |0.873679| = 0.873679 Here, |r| = (=0.873679) > critical value (=0.632). So, we reject the null hypothesis. Conclusion: At 5% level of significance, there is sufficient evidence to support the claim that there is a linear correlation between the number of chirps in 1 minute and temperature.