A teacher has found that his class performed particularly well on a quiz when the material wasrelated to pop culture (M= 77) compared with normal quiz performance (u= 69, 0 =20 ). What isthe effect size for this effect?Select one:• a. 0.40e b. 1.57• c. 0.94• d. -0.94e e. All of the above

Given information- M = 77 μ = 69 σ = 20 Effect size is the just standardized mean difference between…

Answered: A teacher has found that his class…

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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Similar questions

Using the below data, how will you judge the degree of correlation between the two variables x and y? Edxdy = 125 n =60 Ox=5 Cy = 7 O a. Very high degree of correlation O b. Very low degree of correlation O C. Perfect correlation O d. No correlation
I use excel. I do not know what data anlysis toolpak to use, however, to find the answer, t stat, df, P, etc. I also don't know how to word Ho and Ha. Thanks! The data shown below are the initial weights and gains in weight (in grams) of female rats on a high protein diet from 24 to 84 days of age. The point of interest in these data is whether the gain in weight is related to (dependent on) the initial weight. If so, then feeding experiments on female rats can be made more precise by adjusting for differences in initial weights of the rats. Statistically test this with a regression analysis. Rat Number Initial Weight (gms) Weight Gain (gms) 1 50 128 2 64 159 3 76 158 4 64 119 5 74 133 6 60 112 7 69 96 8 68 126 9 56 132 10 48 118 11 57 107 12 59 106 13 46 82 14 45 103 15 65 104 What is the equation for the multiple regression? What is the best estimate of the amount of variance in Y which is due to its regression on the independent variables?
Which value of r indicates a stronger correlation: r=0.797 or r= -0.922? Explain your reasoning. Choose the correct answer below. C ⒸA. r= -0.922 represents a stronger correlation because | -0.922|>10.7971. OB. r= -0.922 represents a stronger correlation because 0.797> -0.922. OC. r=0.797 represents a stronger correlation because 0.797 > -0.922. OD. r=0.797 represents a stronger correlation because | -0.922|>10.7971.
A scatterplot is made of the average height (x axis) and average blood temperature (y axis) of 200 different mammals. The correlation is medially positive, approximately around r = 0.6. Human is at the 2 SD below the average on height and approximately 1.2 SD below the average on blood temperature. This implies this point is... Group of answer choices No answer text provided. on the SD line it is impossible to say with the information given on the regression line
The correlation between midterm and final grades for 300 students is 0.620. If 5 points are added to each midterm grade, the new r will be: a. 0.124 b. 0.57 c. 0.62 d. 0.744
Solve these 4 questions please using the data table below
Interpret the effect size (n2) for the following: t(90)= 4.06, p = .001, n2 = .11
Which value of r indicates a stronger correlation: r= 0.841 or r= - 0.949? Explain your reasoning. Choose the correct answer below. O A. r= 0.841 represents a stronger correlation because -0.949 > 0.841|. B. r= - 0.949 represents a stronger correlation because -0.949|> |0.841|. C. r= - 0.949 represents a stronger correlation because 0.841 > - 0.949. D. r= 0.841 represents a stronger correlation because 0.841 > - 0.949.
Would A be the answer?
Suppose the correlation between height and weight for adults is +0.80. What proportion of the variability in weight can be explained by the relationship with height? A. 20% B. 36% C. 64% D. 80%
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
A veterinarian collects data about puppies in her practice. She makes a scatterplot with their age in days on the horizontal axis and weight in ounces (oz) on the vertical axis and sees that the scatterplot is football shaped. The average age of the puppies is 42 day, with an SD of 7 days. The average weight is 25 oz, with an SD of 5 oz. The correlation is moderately strong, with r = 0.7. 4. (a) The age of two puppies differ by 20 days. The difference in their weight is predicted to be oz. (b) The baseline prediction for the weight of puppies ignores their age and just uses the information from all puppies. The baseline predicted weight is oz and the RMS error for this prediction is o. (c) Suppose we converted the units of age from days to weeks. The average age is now weeks, with an SD of weeks. The correlation between age in weeks and weight in oz is now r =

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