Resercher conducted an observational study on the age of a person and the amount of money a personpends on greenes each week. The researchers reported a correlation coefficient of r=-0.97 for the twoTarnblis. Wich satement is a aprpriate interpretation of the relationship between a person's age andthe amount of money spent on groceries?O The neaive vaue of r indicates there is no relationship between age and money spent.O The negative value of r ndicates that age causes a person to spend more on groceries.O The value of r indicates that the relationship is weak, and as age increases, the money spentnCreases.O The value of r indicates that the relationship is strong, and as age increases, the money spentdecreases.Answer the question above by

Correlation coefficient quantifies the strength of relationship between two variables. Correlation…

Reserchers conduted an observational study on the age of a person and the amount of money a person pends on grenes each week. The researchers reported a correlation coefficient of r =-0.97 for the two varable. Wich satemen i a apopriate interpretation of the relationship between a person's age and the amount of money spent on groceries? The negaive ralue of r indicates there is no relationship between age and money spent. O The negative value of r indicates that age causes a person to spend more on groceries. O The vale of r indicates that the relationship is weak, and as age increases, the money spent increases The value of r indicates that the relationship is strong, and as age increases, the money spent decreases Aswer fhe question abo

Reserchers conduted an observational study on the age of a person and the amount of money a person pends on grenes each week. The researchers reported a correlation coefficient of r =-0.97 for the two varable. Wich satemen i a apopriate interpretation of the relationship between a person's age and the amount of money spent on groceries? The negaive ralue of r indicates there is no relationship between age and money spent. O The negative value of r indicates that age causes a person to spend more on groceries. O The vale of r indicates that the relationship is weak, and as age increases, the money spent increases The value of r indicates that the relationship is strong, and as age increases, the money spent decreases Aswer fhe question abo

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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The accompanying table shows the ages (in years) of 11 children and the numbers of words in their vocabulary. Complete parts (a) through (d) below. Click here to view the data table. Click here to view the table of critical values for the Pearson correlation coefficient. ... Interpret the correlation. Choose the correct answer below. O A. Aging causes the number of words in children's vocabulary to increase. B. Based on the correlation, there does not appear to be any relationship between children's ages and the number of words in their vocabulary. O C. Based on the correlation, there does not appear to be a linear relationship between children's ages and the n O D. Aging causes the number of words in children's vocabulary to decrease. CE. As age increases, the number of words in children's vocabulary tends to increase. there is a significant linear correlation O F. As age increases, the number of words in children's vocabulary tends to decrease. there is no correlation (d) Use the…
Baseball owners believe that the more runs scored, the higher the attendance. Is there evidence that more fans attend games if the teams score more runs? Data collected midway through the season indicate a correlation of 0.848 between runs scored and the number of people at games. a) Does the scatterplot indicate that it's appropriate to calculate a correlation? Explain. O A. Yes, because the relationship between number of runs scored and attendance appears to be straight. O B. Yes, because the association between the number of runs scored and attendance is positive. 37500- OC. No, because there are too many outliers for a numerical correlation to be appropriate. 30000- O D. No, because the number of runs scored and attendance are not quantitative variables. b) Describe the association between attendance and runs scored. 22500- 320 360 400 440 480 O A. The association between attendance and runs scored is negative, straight, and moderate. Runs O B. The association between attendance…
The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. 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. Should we expect that there would be a correlation? Use a significance level of α = 0.01. Click the icon to view the ages of the award winners. 70- 20- 20 70 Best Actress (years) 20- 20 70 Best Actress (years) The linear correlation coefficient is r= -0.248. (Round to three decimal places as needed.) Determine the null and alternative hypotheses. = 0 Ho: P H₁:p # 0 (Type integers or decimals. Do not round.) The test statistic is t = (Round to two decimal places as needed.) ... 70- 20- al 20 70 Best Actress (years) Best Actor (years) 60 70- H HHHH HE 20- 20 Best Actress (years) 70 S 3
To examine the linear correlation between adult age and weight, data was collected from 9 adults. See the table below. Age Weight (Years) (pounds) 26 203 28 245 29 141 34 139 39 199 40 194 41 137 50 181 52 197 Does this result suggest that the correlation is statistically significant? Use a = 0.01. Important Note: Round your value for r to three decimals before computing the STS. DO NOT use the built- in LinRegTTest on a calculator because you might get marked wrong. When computing the P-value, use the rounded STS. 1. Select the correct statement: O f the correlation is found to be statistically significant, that means that changes in æ cause changes in y O Even if the correlation is found to be statistically significant, that does not necessarily mean that changes in æ cause changes in y
An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height. To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated. Identify the correct null hypothesis A. H0: There is no relationship between leg power and jump height B. H0: There is a relationship between leg power and jump height C. HA: There is a relationship between leg power and jump height D. HA: There is no relationship between leg power and jump height
The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. 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. Should we expect that there would be a correlation? Use a significance level of α=0.05. LOADING... Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. A. 20702070Best Actress (years)Best Actor (years) A scatterplot has a horizontal axis labeled Best Actress in years from 20 to 70 in increments of 5 and a vertical axis labeled Best Actor in years from 20 to 70 in increments of 5. Twelve points are plotted. Eleven of the plotted points follow the pattern of a line rising from left to right passing through the points (24, 38) and (66, 58). An…
An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height. To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated. What does this type of correlation indicate about how leg strength and jump height change together? A. Both leg strength and jump height increase and decrease together B. There is no relationship between leg strength and jump height C. As leg strength increases, jump height decreases D. As jump height increases, leg strength decreases
The older that an adult tends to be before deciding to get married, the longer the person's marriage tends to last. What type of correlation exists between age of marriage and the number of years the marriage lasts? A. positive B. negative
Complete the following instructions:i. Identify the independent and dependent variables.ii. Calculate and interpret the Pearson correlation coefficient r for the paired data. Be sure to indicate if the correlation is positive or negative, and whether it is strong, moderate, or weak, or if there does not appear to be any significant correlation. A researcher for a gasoline retailer examines the relationship between the volume of gasoline purchased in kL(i.e. 1000 L) compared to the price of gasoline (in $/L), over a course of several days, to see if there is a correlation between the data: Amount of Gasoline Purchased Price of Gasoline 2.257 1.079 3.126 1.015 2.793 1.046 4.671 0.973 2.137 1.021 5.916 0.939 2.775 0.995 4.88 0.927 3.162 0.964 7.498 0.899 2.971 0.982 3.596 0.945 1.372 1.129 3.961 1.059 i. Independent Variable: Dependent Variable: ii. Pearson correlation coefficient (r): Round to 3 decimal…
A study of elementary school children, ages 6 to 11, finds a high positive correlation between shoe size x and score y on a test of reading comprehension. The observed correlation is most likely due to: the effect of a lurking variable, such as age or years of reading experience. a mistake, because the correlation must be negative. cause and effect (larger shoe size causes higher reading comprehension). reverse cause and effect (higher reading comprehension causes larger shoe size).
Each given statement contains a blunder. In cach case, choose the statement that correctly explains the blunder. "There is a high correlation betwoen the "We found a high correlation (= 109) "The correlation between height and sex of American workers and their between students' ratings of faculty teaching and ratings made by other faculty members." weight of the subjects was 0.63 income." centimeters."
An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height. To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated Interpret r. What type of correlation exists between leg strength and jump height? A. A negative correlation B. No correlation C. A positive correlation D. We cannot know based on the available information