Product Calories Sugar A 340 13.3 B 430 2.8 C 450 25.3 D 500 26.6 E 530 19.2 F 580 26.0 G 590 23.2
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|
Product
|
Calories
|
Sugar
|
|
|---|---|---|---|
|
A
|
340
|
13.3
|
|
|
B
|
430
|
2.8
|
|
|
C
|
450
|
25.3
|
|
|
D
|
500
|
26.6
|
|
|
E
|
530
|
19.2
|
|
|
F
|
580
|
26.0
|
|
|
G
|
590
|
23.2
|
a. Compute the
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- Find quartile 2 (Q2) of the data set. {-4, -6, -9, -3, -2, -4, 0} -4 -2 O -6 O Type here to search F2 F3 F4 F5 F6 F7 F8 F9 F10 FL F1 @ %23 2$ & 2 3 4 6 7 8. 9 W E R Y A D F G H JCan balloons hold more air or more water before bursting? A student purchased a large bag of 12-inch balloons. He randomly selected 10 balloons from the bag and then randomly assigned half of them to be filled with air until bursting and the other half to be filled with water until bursting. He used devices to measure the amount of air and water was dispensed until the balloons burst. Here are the dataThe owner of a new car conducts a series of six gas mileage tests and obtains the following results, expressed in miles per gallon: 3., 22.7, 21.4, 20.6, and 21.4. 20.9. Find the mode for these data.
- The following data was collected to explore how the average number of hours a student studies per night and the student's GPA affect their ACT score. The dependent variable is the ACT score, the first independent variable (x1�1) is the number of hours spent studying, and the second independent variable (x2�2) is the student's GPA. Effects on ACT Scores Study Hours GPA ACT Score 55 44 3030 44 33 3030 33 33 1919 33 33 1818 22 22 1818 Copy Data Step 1 of 2 : Find the p-value for the regression equation that fits the given data. Round your answer to four decimal placesDetermine which plot shows the strongest linear correlation. S OA. 7 X 4 4 H O C. # 3 80 F3 E D C $ 4 R F % 5 V T G 6 MacBook Air B FO Y H & 7 U N OB. OD. * 8 J DII 1 0 46 M ( 9 YA O K DD F9 O ) < 20 O 1 L F10 Time Remaining: 01:59:07 P .v command .... 6 FI I { [ ? option 1 Next ] dTable #10.1.6 contains the value of the house and the amount of rental income in a year that the house brings in ("Capital and rental," 2013). Find the correlation coefficient of determination and then interpret both Table #10.1.6: Data of House Value versus Rental Value Rental Value Rental Value Rental Rental Value 67500 81000 6656 77000 4576 75000 7280 6864 95000 7904 94000 8736 90000 6240 85000 7072 121000 12064 115000 7904 110000 7072 104000 7904 135000 8320 130000 9776 126000 6240 125000 7904 145000 8320 140000 9152 7488 9568 140000 135000 7488 165000 13312 165000 8528 155000 148000 8320 178000 11856 174000 10400 170000 9568 170000 12688 匯 190000 200000 225000 8320 12272 8528 200000 200000 10608 194000 11232 8320 10400 11648 10192 12272 10400 200000 240000 214000 208000 240000 10192 240000 12064 12480 244500 11232 12896 12480 289000 11648 270000 262000 325000 12480 310000 303000 300000 12480
- Hi. PLease note I already asked this question and received the wrong answer. Jobs and productivity! How do retail stores rate? One way to answer this question is to examine annual profits per employee. The following data give annual profits per employee (in units of 1 thousand dollars per employee) for companies in retail sales. Assume σ ≈ 3.6 thousand dollars. 3.9 6.5 4.5 8.7 7.5 5.2 8.3 5.9 2.6 2.9 8.1 −1.9 11.9 8.2 6.4 4.7 5.5 4.8 3.0 4.3 −6.0 1.5 2.9 4.8 −1.7 9.4 5.5 5.8 4.7 6.2 15.0 4.1 3.7 5.1 4.2 (a) Use a calculator or appropriate computer software to find x for the preceding data. (Round your answer to two decimal places.) thousand dollars per employee(b) Let us say that the preceding data are representative of the entire sector of retail sales companies. Find an 80% confidence interval for μ, the average annual profit per employee for retail sales. (Round your answers to two decimal places.)…The authors of a paper were interested in how the distance a deer mouse will travel for food is related to the distance from the food to the nearest pile of debris. Distances were measured in meters. The data and computer output are given below. Distance from Debris Distance Traveled 6.94 0.00 5.23 6.13 5.21 11.29 7.10 14.35 8.16 12.03 5.50 22.72 9.19 20.11 9.05 26.16 9.36 30.65 Simple Linear Regression Results: Dependent Variable: Traveled Independent Variable: Debris Sample size: 9 R (correlation coefficient) = 0.5657 R-sq = 0.32002088 Estimate of error standard deviation 8.670711 Parameter estimates: Parameter Estimate Std. Err. Alternative DF T-Stat P-Value Intercept -7.6854587 13.332196 ≠ 0 7 -0.5764586 0.5824 Slope 3.2340908 1.7818117 ≠ 0 7 1.8150575 0.1124 a)What is the least squares regression line for the output given above? b) what is the predicted traveled distance given the distance from debris is 6.5 meters?The data below is provided by the local ice-cream shop that keeps track of how many ice-creams aresold versus the temperature on that day. Here are the figures for the last 7 days. Let x; represent thetemperature ofthe respective days and let /; represent the ice cream sales on the respective days'Day I 2 3 4 5 6 7Ice cream Temp oC 14.2 16.4 l l.9 15.2 18.5 22.1 19.4Sales (N$) 215 325 185 332 406 s22 412Required:i. Compute and interpret the sample covarianceii. Compute and interpret the sample correlation coefficient
- The following data refers to yield of tomatoes (kg/plot) for four different levels of salinity. Salinity level here refers to electrical conductivity (EC), where the chosen levels were EC = 1.6, 3.8, 6.0, and 10.2 nmhos/cm. (Use i = 1, 2, 3, and 4 respectively.) 1.6: 59.4 53.4 56.3 63.2 58.4 3.8: 55.9 59.7 52.7 54.2 6.0: 51.7 48.2 53.9 49.0 10.2: 44.3 48.3 40.7 47.2 46.7 W23 = W 24 = W34 = USE SALT Apply the modified Tukey's method to identify significant differences among us. (Round your answers to two decimal places.) W12 = W13 = W14= Which pairs are significantly different? (Select all that apply.) Othe group and the 3.8 group the 1.6 group and the 6.0 group the 1.6 group and the 10.2 group the 3.8 group and the 6.0 group the 3.8 group and the 10.2 group O the 6.0 group and the 10.2 group There are no significant differences.Find the Pearson product-moment correlation coefficient of the data set shown below:Where the car price is Y and car age is the X. Car Age (in years) Price in dollars 4 6300 4 5800 5 5700 5 4500 7 4500 7 4200 8 4100 9 3100 10 2100 11 2500 12 2200
