A professor wanted to study whether there was an association between a person's ageand their likelihood to use social media. He surveyed members of Gen Z, Millennials, and Gen X.Below you will find the data that was collected:YES, use social mediaNO, do not use social mediaH₂:a=0.05 DF=_Gen Z7811a. Perform a Chi-Square Test for Association to see if there is evidence to show there is anassociation between age and likelihood to use social media?Ho:Conclusion:b. Fill in the blanks using your table:X²=Circle one:Millennials12419Number of Gen Z that use social media=Total number of Gen Z surveyed =Gen X7924P-value=Fail to Reject H. OR Reject Hoc. Use your survey results from part b to find a one-sample 95% confidence interval.d. According to an October 2022 study, approximately 93% of Generation Z use social mediaplatforms. Does your confidence interval support or refute this claim?

The question is about categorical data analysis Given : To find : a ) chi sq. test for…

Answered: A professor wanted to study whether…

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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Kris works for the MESA Air Pollution Study at UW, and studies the correlation be- tween air pollution and the disease atherosclerosis. Nationally, 40% of adults suffer from atherosclerosis. Kris suspects that the proportion of people with atherosclerosis in high- pollution areas is higher. In a random sample of 600 residents of high-pollution areas, he finds that 270 (45%) subjects have atherosclerosis. At the 1% level (α = .01), is this good evidence that people in high-pollution areas are more likely to have atherosclerosis? (a) Which of the following is the Ha ? (research claim or alternate) A. Ha : p ≥ 0.40 B. Ha : pb ≥ 0.40 C. Ha : p > 0.40 D. Ha : p > b 0.40 E. Ha : p > b 0.45 F. Ha : p > 0.45 G. Ha : pb ≥ 0.45 H. Ha : p ≥ 0.45 I. None of these Hint: First read the problem and using my notes (or Hawkes) for 9.1, set up H0 and Ha . Then pick the right Ha from the above list. Dont try to guess the answer from the above list. (b) Which of the…
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
Warren wants to know if the amount of coffee that you drink is related to the number of hours that you stay awake. He recruits 50 participants using random sampling to report how much coffee they drank and the time of the day that they went to sleep. He then performs a correlation to determine the association between the amount of coffee that was consumed and the number of hours that they stayed awake. There was a statistically significant positive correlation between amount of coffee that participants drank and the number of hours that they stayed awake, r(49) = .82, p < .05, two-tailed, r2 = .08. This was a small effect – 8% of the variance in the amount of coffee drank is explained by hours that you stay awake (and vice versa).
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
In 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 correlation between mean 2015 Mathematics SAT scores and mean 2015 Writing SAT scores for all 50 states and the District of Columbia is 0.983.0.983. Would one expect the correlation between the mean state SAT scores for these two tests to be lower, about the same, or higher than the correlation between the scores of individuals on these two tests?
A survey of property owners' opinions about a street-widening project was taken to determine if owners' opinions were related to the distance between their home and the street. A randomly selected sample of 100 property owners was contacted and the results are shown next. Opinion Front Footage For Undecided Against Under 45 feet 12 4 4 45-120 feet 35 5 30 Over 120 feet 3 2 5 What is the expected frequency for people against the project and who have over 120 feet of property foot-frontage? Select one: a. 1.1 b. 3.9 c. 5.0 d. 5.5
determine whether suicide and homicide rates in metropolitan areas around the country are correlated. a sample of 10 metropolitan areas with their rates (number per 100,000), of suicide and homicide. computed the correlation coefficient of 0.70.
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
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).
What is the correlation between a person's income and their level of education, and to what extent does this relationship vary across different demographic groups such as race, gender, and age?
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

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