a) Suppose the weight loss for sample A be denoted by Xa and the population mean of the weight loss corresponding to sample A be Ma. Then, we want to test
H0: Ma = -5 vs H1: Ma>-5
One-Sample
Test
Test Value =
-5
95% Confidence Interval of the Difference
t df Sig. (2-tailed) Mean Difference Lower
Upper
SampleA 1.679 29 .104 1.86667
-.4073 4.1406
Since, the p-value is 0.104 which is greater than 0.05, the null hypothesis can not be rejected at 5% level of significance. Hence, mean weight loss is not -5.
b) Here also the hypothesis is the same as above. The result is given below:
One-Sample
Test
Test Value =
-5
95% Confidence Interval of the Difference
t df Sig. (2-tailed) Mean Difference Lower
Upper
SampleC -2.280 29 .030 -6.33333
-12.0152 -.6514
Since, the p-value is 0.03 which is less than 0.05, so the null hypothesis is rejected at 5% level of significance and we can conclude that the average weight loss is significant.
c) The difference of sample mean (weight loss) and proposed value (-5) is 1.8667 for sample A, whereas it is -6.3333 for sample C. 95% confidence interval for sample A does not contain the point -5, both the lower and upper confidence limits are greater than -5. So, the test is insignificant for sample A.
For sample C, the 95% CI does not contain the point -5, and also both the upper and lower confidence limits are smaller than -5. Hence, in this case, the test is significant.
Show all work Question 6 3 pts Using Case Study D, which of the following is the best way to organize the data for the NPZ-8 scores with a class width of 3? 04:59: 10-14 0-2; 3-5; 6-8; 9-11; 12-14 20Frequency%20Distributions%20&%20Histograms%20 Tables.pdf TABLE 2.10 Nurse Sick Nurse Sick Nurse Sick Number Days Number Days Number Days 15 16 17 18 19 7 20 21 14 TABLE 2.11 App. 16 18 App. m 220 225 f135 137 f 180 201 m...
Show all work and explain × | M Inbox (x UB Quiz: Lab 1- x cture es/ /1631958/quizzes/2791381/take D Question 8 Would you characterize the distribution above as being positively (right) skewed, or symmetric? O positively (right) skewed O negatively (left) skewed O symmetric ion 9 3 pts pdf biostats.pdf TABLE 2.10 Nurse Sick Nurse Sick NurseSick Number Days Number Days Number Days 15 8 16 8 17 18 19 7 20 7 614 8 2 TABLE 2.11 App App...
4 pts Question 2 What is the relative frequency of nurses using at least 4 but no more than 6 sick days? (Enter as a decimal rounded to two decimal places) Window Help abi-FX @ Course c x|囚Ausif Ma × Expedia × 目Untitled × 01%20-%20Frequency%20Distributions%20&%20Histograms%20 Tables.pdf | expe。 TABLE 2.10 Nurse Sick Nurse Sick Nurse Sick Number Days Numher Days Number Days 10 6 18 12 4 13 7 20 TABLE 2.11 App. App Numb. Gender Ws Wp Numb. Gender...
Show work and explain please %20.%20Frequency%20Distributions%20&%20Histograms%20Tables.pdf TABLE 2.10 Nurse Sick Nurse Sick Nurse Sick Number Days Number Days Number Days 9 8 16 I1 12 13 14 18 21 TABLE 2.11 App Numb. Gender Ws Wp Numb. Gender Ws Wp m 220 225 f 135 137 f 180 201 m 210 205 f 145 144 f 131 133 m 177 180 m 135 135 m 183 180 m 165 166 f 160 166 m 178 180 m 155 152 155...
%201%20-%20Frequency%20Distributions%20&%20H.stograms%20Tables.pdf TABLE 2.10 Nurse Sick Nurse Sick Nurse Sick Number Days Number Days Number Days 8 17 18 3 19 7 20 12 14 TABLE 2.11 App App. Numb. Gender Ws Wp Numb. Gender Ws Wp 165 167 16 m 220 225 f 135 137 f 180 201 m 210 205 f 145 144 f131 133 m 177 180 m 135 135 m 183 180 m 165 166 m 215 210 17 m 190 186 f 115 111 19 m...
The accompanying table provides data for the sex, age, and weight of bears. For sex, let 0 represent female and let 1 represent male. Letting the response (y) varieble represent weight, use the dummy variable of sex and the variable of age and to find the multiple regression equation, Use the equation to find the predicted weight of a bear with the characteristics given below. Does sex appear to have much of an effect on the weight of a bear?...
Read the following data ID Sex Age Height Weight Pulse FastGlucose PostGlucose 2304 F 16 61 102 100 568 625 1128 M 43 71 218 76 156 208 4425 F 48 66 162 80 244 322 1387 F 57 64 142 70 177 206 9012 F 39 63 157 68 257 318 6312 M 52 72 240 77 362 413 5438 F 42 62 168 83 247 304 3788 M 38 73 234 71 486 544 9125 F 56 64...
You will start by considering the data set in the proj2-2.txt file on BlackBoard. The data set contains SEX (1=female; 2=male), PEFR in l/min and height in cm. 1. Make a scatter plot of PEFR versus height. 2. Fit the simple linear regression of PEFR on height. 3. What is the estimated slope (with CI) and the interpretation of this estimate. 4. What is the standard deviation around the line (with CI) and the interpretation of this estimate. 5. Estimate...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about fifteen boys Derive a multiple regression formula and its multiple correlation coefficient about objective variable that is distance of ball throw (y) Furthermore, derive distance of 10 ball y [m] about a x1-45[kg], x2=158[cm] and x3=60[kg] by using the multiple regression formula Stature Weight| Grip boll throw y[m] x1[kg]x2cm] x3[kg] Distance of 34 22 28 146 36 57 46 169 24 39 25 160...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about fifteen boys Derive a multiple regression formula and its multiple correlation coefficient about objective variable that is distance of ball throw (y) Furthermore, derive distance of 10 ball y [m] about a x1-45[kg], x2=158[cm] and x3=60[kg] by using the multiple regression formula Stature Weight| Grip boll throw y[m] x1[kg]x2cm] x3[kg] Distance of 34 22 28 146 36 57 46 169 24 39 25 160...