In a study of a representative group of men, the correlation between height and weight was 0.43. One man in the study was both two SDS above average in height and two SDS above average in weight. His weight will be Ogreater than O less than O about equal to the estimated average weight of all men of his height in the study.
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- Among a random sample of the stat's census deciles (a small geographic unit), there is a -0.90 correlation (p=.50) between school truancy rates and the rates of alcohol sales to minors. How would you characterize the relationship between truancy and alcohol sales to minors? A. We cannot be confident that there is a relationship between the two variables. B. We have evidence that there is a strong, positive correlation between the two variables. C. We have evidence that there is a strong, negative correlation between the two variables. D. We have evidence that there is a weak, positive correlation between the two variables. E. We have evidence that there is a weak, negative correlation between the two variables.For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of twelve types of automobile, the linear correlation coefficient is found and the P-value is 0.022. 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 %, which is so there sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles. (Type an integer or a decimal. Do not round.)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
- 2. A researcher measures the relationship between temperature and freeway traffic, with a correlation of -0.61. We would say this relationship is: Negative and Moderate Negative and Strong Positive and Moderate Positive and Weak O o o OAn 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 decreasesIn a study examining the relation of math ability to the belief that math ability was innate, the belief was considered the predictor variable. The researcher hopes to find a correlation between the participants’ math ability and their belief that math ability is innate. The scores for the three participants are shown below. The group that believed that math is NOT innate scored 66, 70, 50. The group that believed that math IS innate scored 7, 4,10. Calculate, by hand, the correlation between these two variables. Is it positive or negative and is it a strong correlation?
- The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technologgy was also given a foot length of 10.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 10.8 cm, what is the single value that is the best predicted height for that person? H Click the icon to view the technology output. The single value that is the best predicted height is cm. Technology Output (Round to the nearest whole number as needed.) The regression equation is Height - 67.5 +5.15 Foot Length Predictor Coef SE Coef Constant 67.52 11.07 6.10 0.000 Foot Length 5.1508 0.4817 10.69 0.000 S-5.50271 R-Sq = 73.18 R-Sq (adj) = 72.44 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 954 PI 123.149 1.605 (119.732, 126.566) (111.996, 134.302) Values of Predictors for New…A teacher always inculcates the value of honesty and making efforts to achieve quality of work/output. With this, a basic research was conducted. The correlation coefficient r between the number of hours spent by the learners in studying and their academic performance was found to be 0.97. Based on the finding, which of the following best describe the result? O a. There is a strong positive correlation between the number of hours spent by the learners in studying and their academic performance. As a learner spends more time in studying, the higher is their academic performance. O b. There isa strong negative correlation between the number of hours spent by the learners in studying and their academic performance. As a learner spends more time in studying, the lower is their academic performance. O c. There is a perfect correlation between the number of hours spent by the learners in studying and their academic performance. As a learner spends more time in studying, the higher is their…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).
- A data set contains information on the grams of fat and number of calories in 25 different fast foods. The correlation coefficient between fat content and calories is determined to be 0.69. Calculate the p-value for the test of significance.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 informationMs. Long studied her students' physics test scores and sleeping habits. She found that students who slept less tended to earn lower scores on the test. What conclusion should she make? There is no correlation between test score and amount of sleep. There is a correlation between test score and amount of sleep. There is probably also causation. This is because there is a decrease in a student's test score with a decrease in the amount of sleep. There is a correlation between test score and amount of sleep. There may or may not be causation. Further studies would have to be done to determine this.