08Siti has created a dataset containing 10 rows of data, each row signifies one person. She hastwo variables, the first is Age (in years) and the other is Cholesterol levels (in mmol/L). Shewants to find out if there is any relationship between these two variables using the Pearsoncorrelation in SPSS.a) State the null and alternative hypotheses.b) Based on the Pearson correlation results below from SPSS, make a decision regardingthe null hypotheses.AgePearson CorrelationSig. (2-talled)NAge110.882Cholesterol Pearson CorrelationSig. (2-talled)NCorrelation is significant at the 0.01 level (2-talled).Cholesterol.882.00110.00110110

There are 2 variables. The first is Age (in years) and the other is Cholesterol levels (in mmol/L).…

Answered: 08 Siti has created a dataset…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Technology output The single value that is the best predicted height is cm. (Round to the nearest whole number as needed.) The regression equation is Height = 65.9 + 4.97 Foot Length Predictor Сoef SE Coef T P Constant 65.93 11.53 5.72 0.000 Foot Length 4.9691 0.4803 10.35 0.000 S = 5.50572 R-Sq=71. 5% R-Sq(adj) = 70.8% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 214.506 1.768 (210.408, 218.604) (202.711, 226.301) Values of Predictors for New Observations Foot New Obs Length 29.9
Compute the correlation coefficient between the price of eggs and the price of milk. Round the answer to at least three decimal places.
A set of n=4 pairs of X and Y value has SSx=6, SSy=18, and SP=9, for these data, what is the pearson correlation?
We made a survey with the number of people in a household and the number of times they get sick throughout the year. In a household, 3 people get sick once, 4 people get sick twice, 2 people get sick three times and 1 person gets sick 4 times. 1) Give the correlation coefficient, proper interpretation of it, and explain the relevance to the topic
A researcher measures GPA and height for a group of high school students. What kind of correlation is likely to be obtained for these two variables?
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
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
If the linear correlation coefficient is 0.546, what is the value of the coefficient of determination?
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 technology was also given a foot length of 23.5 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 23.5 cm, what is the single value that is the best predicted height for that person? The single value that is the best predicted height is _____cm. The regression equation is Height=50.8+3.20 Foot Length Predictor Coef SE Coef T P Constant 50.82 11.65 4.36 0.000 Foot Length 3.1982 0.4903 6.52 0.000 S=5.50372 R-Sq=71.7% R-Sq(adj)=71.0% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 125.978 1.744 (121.356, 130.600) (114.681, 137.275) Values of Predictors…
Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support Correlation Results the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that Correlation coeff, r: 0.959614 a measured chest size can be used to predict the weight? Use a significance level of = 0.05. Critical r: +0.2680855 P-value (two tailed): 0.000 Но: Р H1:P (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) O A. There is one critical value at r= . B. There are two critical values at r= ± Is there sufficient evidence to support the claim that there is a linear correlation between…
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 technology was also given a foot length of 17.8 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 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…
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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