Annual high temperatures in a certain location havebeen tracked for a sample of 7 years. Let X representthe year and Y the high temperature (in C°).x567891011r =Calculate the correlation coefficient. (Round to threedecimal places.)y23.4526.0226.7931.0630.5333.834.07Let's test the significance of the correlationcoefficient at a = 0.01 significance level.Ho: There is not a significant relationship between theyear and high temperature, i.e., p = 0.Ha: There is a significant relationship between theyear and high temperature, i.e., p = 0.a. Calculate the test statistic. Round to threedecimal places.t=b. Calculate the p-value. Round to four decimalplaces.p-value =

The data shows the year and the high temperature for a sample of 7 years.

Answered: Annual high temperatures in a certain…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Caffeine (mg) Sleep (hours) 60 8 0 8 220 5.5 100 7 80 6.5 For caffeine intake, the mean is 92 and the standard deviation is 80.75. For sleep, the mean is 7 and the standard deviation is 1.06. Calculate the linear correlation coefficient r by hand for this set of paired data values using r=(z_x-z_y)/(n-1). Show your work. Is the value of r statistically significant? Use Pearson's r table to justify your answer. Does the value for r and the statistical significance indicate a positive linear correlation, a negative linear correlation, or no linear correlation between the variables caffeine intake and hours of sleep? What does this mean in context?
Suppose the correlation coefficient r=0.16 Find:a. The coefficient of determination r2= (round to 3 decimal places)b. The percentage of explained variation = % (round to 1 decimal place)c. The percentage of unexplained variation = % (round to 1 decimal place)
need help with everything from test statistic and onward. Thx!
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places. Advertising Cost Profit 3 19 4 16 24 6 29 7 25 27 10 30 Ho: p = 0 На: р * 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a O Greater than a The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho The conclusion is O There is a significant negative linear correlation between advertising expense and profit. O There is a significant linear correlation between advertising expense and profit. O There is a significant positive linear correlation between advertising expense and profit. O There is insufficient evidence to make a conclusion about the linear correlation between advertising expense and…
Right arm 102 101 94 79 79 Left arm 175 169 182 146 144 If the sample data were to result in the scatterplot shown here, what is the value of the linear correlation coefficient r?
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit Use a significance level of 0.01 and round all values to 4 decimal places. Advertising Cost Profit 3 21 4 16 5 29 17 7 28 8 21 Ho: p = 0 Ha: p +0 Find the Linear Correlation Coefficient r= Find the p-value p-value = The p-value is Less than (or equal to) a OGreater than a The p-value leads to a decision to Do Not Reject Ho OReject Ho OAccept Ho
Data collected from a sample of 8 students relating study time (x in hours per week) and leisure time (y in hours per week) yielded the information shown below. What is the value of the sample correlation coefficient? Enter your answer accurate to TWO (2) decimal places. X= 59.37 Y = 4.25 SS= 1843.87 SS, = -49.75 SS, = 7.5
The paired data below consists of heights and weights of 6 randomly selected adults. Find the linear correlation coefficient, the linear regression line, and predict the weight of a randomly selected person who is 1.69 meters tall. X Height (meters) 1.61 1.72 1.78 1.80 1.67 1.88 Y Weight (kg) 54 62 70 84 61 92
Calculate Pearson's correlation coefficient using the following values: (image attached)
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