Ticket Price Attendence 6 196 10 103 14 177 18 107 22 112 26 137 30 116 34 143 38 182 Ho: ρ = 0 Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = ? Find the p-value p-value = ?
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The data shown below consists of the price (in dollars) of 7
| Ticket Price | Attendence |
|---|---|
| 6 | 196 |
| 10 | 103 |
| 14 | 177 |
| 18 | 107 |
| 22 | 112 |
| 26 | 137 |
| 30 | 116 |
| 34 | 143 |
| 38 | 182 |
Ho: ρ = 0
Ha: ρ ≠ 0
Find the Linear
r = ?
Find the p-value
p-value = ?
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- 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 significant linear correlation between advertising cost and profit . Use a significance level of 0.10 and round all values to 4 decimal places. Advertising Cost Profit 3 23 4 23 5 22 6 26 7 25 8 25 9 25 10 30 11 31 12 31 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =The data shown below consists of the price (in dollars) of 7 events at a local venue and the number of people who attended. Determine if there is significant linear correlation between ticket price and number of attendees. Use a significance level of 0.01 and round all values to 4 decimal places. Ticket Price 6 10 14 18 22 26 30 r= Ho: p= 0 Ha: p=0 Find the Linear Correlation Coefficient Find the p-value p-value= Attendence 151 146 146 145 The p-value is 138 137 137 O Less than (or equal to) a O Greater than a The p-value leads to a decision to Accept Ho Reject Ho Do Not Reject Ho The conclusion is There is insufficient evidence to make a conclusion about the linear correlation between ticket price and attendance. There is a significant negative linear correlation between ticket price and attendance. There is a significant positive linear correlation between ticket price and attendance. There is a significant linear correlation between ticket price and attendance.Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths and heights of males. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.01. Click to view the data on shoe print lengths and heights. Construct a scatterplot. Choose the correct graf Shoe Print Lengths versus Heights of Males O B. OD. 210- 200- 190- 180- 170- 160- 20 24 28 32 36 40 Shoe Print Length (cm) 210 200 190 180 170 160 2101 200- Shoe Print 190- Length (cm) Height (cm) 176.0 180- 170- 160- 20 24 28 32 36 40 31.4 28.9 181.2 31.5 194.5 Shoe Print Length (cm) 32.3 172.9 30.4 174.0 The linear correlation coefficient is r= 32.9 190.5 (Round to three decimal places as needed.) 31.0 176.6 30.8 170.0 30.5 171.9 32.3 175.5 30.5 200.1 32.6 199.3…
- You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 21 22 39 21 38 18 23 22 79 36 42 22 65 29 Ho: p = 0 Ha: p= 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a Greater than a The p-value leads to a decision to O Reject Ho O Accept Ho O Do Not Reject Ho The conclusion is O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is a significant negative linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…You wish to determine if there is a negative linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 31 23 60 27 33 18 64 36 72 31 65 31 Ho: ρ = 0Ha: ρ < 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho The conclusion is There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. There is a significant positive linear correlation between driver age and number of driver deaths. There is a…You wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 66 20 75 32 44 31 44 36 19 23 65 29 61 22 58 25 71 27 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =
- You wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 64 32 55 30 72 36 34 30 31 18 16 29 21 22 32 18 46 24 46 31 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Greater than αα Less than (or equal to) αα The p-value leads to a decision to Do Not Reject Ho Reject Ho Accept Ho The conclusion is There is a significant linear correlation between driver age and number of driver deaths. There is a significant negative linear correlation between driver age and number of driver deaths. There is a significant positive linear correlation between driver age and number of driver deaths. There is…tab Determine if there is a significant correlation between the sets of data at a 10% significance level. 31 29 57 35 60 62 49 62 50 35 37 32 57 20 X y 55 38 Negative Critical Value, tcrit Submit Question esc Positive Critical Value, tcrit Test Statistic, ttest C 2 F Test Conclusion: Reject Ho. There is enough evidence to suggest a significant (positive or negative) linear correlation between the data sets. W = Fail to Reject Ho. There is not enough evidence to suggest a significant (positive or negative) linear correlation between the data sets. 3 H [three decimal accuracy] [three decimal accuracy] [three decimal accuracy] a E A 4 do *5 R T < 6 YYou wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 21 19 27 20 58 31 77 31 47 24 50 26 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Greater than αα Less than (or equal to) αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho
- You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 65 27 34 27 76 24 55 34 71 21 49 24 34 36 27 19 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho The conclusion is There is a significant positive linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. There is a significant negative linear correlation between driver age and number of driver deaths. There is insufficient evidence to make a…The data below was taken from the fat (g) and sodium (mg) found in different types of food found at fast food restaurants. 19 31 34 35 39 39 43 _y 920 1310 860 1180 940 1260 1500 a) Find the p-value to determine if there is a linear correlation between fat (g) and sodium (mg). Record the p-value below. Round to four decimal places. p-value = b) Is there a linear correlation between fat (g) and sodium (mg)? c) If there is a linear correation, write the correlation coefficient below. Otherwise, leave it blank. Round your final answer to four decimal places. d) If there is a linear correlation, write the regression equation below. Otherwise, leave it blank. Round all numbers to four decimal places. e) Using the data shown above, predict the the sodium found in fast food when the fat is 32 g. Round your final answer to two decimal places. f) If there is a linear correlation, what percentage of variation in sodium (mg) can be explained by fat (g)? If there is not a linear correlation, leave…You wish to determine if there is a negative linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 22 20 53 25 19 30 35 23 71 26 36 21 48 25 19 28 Ho: ρ = 0Ha: ρ < 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Greater than αα Less than (or equal to) αα The p-value leads to a decision to Accept Ho Do Not Reject Ho Reject Ho The conclusion is There is a significant linear correlation between driver age and number of driver deaths. There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant positive linear correlation between driver age and number of driver deaths.…
