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- 3 0 The margin of error for a 95% interval estimate for the population slope parameter Is: I: 1.033 343 c 0.925 344 d 0.786 3'45 34.7 a -10.211 348 b 43.190 349 c -8.271 350 d 4.444 351 352 353 a 2.169 35'4- b 2.603 355 c 3.123 d 3.748 A B C D E F G H K L M N O P Q R S 315 24 The model predicts that when raising the price by $1, sales would change by $_ thousand. 316 a -11.113 317 b -10.002 318 c -9.002 319 d -8.101 320 321 25 The predicted sales for a price of $6.00 per burger is $ thousand. 322 a 83.207 323 b 79.047 324 C 75.095 325 d 71.340 326 327 26 Given that E(y -y)? = 1572.444 828 the sample data show that fraction of variations is sales is explained by price. 329 0.508 330 0.432 331 0.367 332 d 0.312 333 334 27 The regression result shows the observed sales deviate from the predicted sales, on average, by $ thousand. 335 a 7.373 336 b 6.267 337 5.327 338 d 4.528' . 2 2 The national obesity statistics Indicates that 44% of adults In the United States are obese. In a random sample of n = 950 adults in Indiana, the proportion who were obese was 1! = 0.459. Does the sample provide significant evidence that the obesity rate In Indiana Is grater than the national rate? The P-value for the this test is . a 0.033 Reject Ha. Conclude the proportion of adults In Indiana who are obese is greater than the national proportion. b 0.046 Reject Ha. Conclude the proportion of adults In Indiana who are obese is greater than the national proportion. c 0.1 1') [Jo not reject u. Do not conclude the proportion of adults in Indiana who are obese is greater than the national proportion. d 0.1 51 [Jo not reject HE. Do not conclude the proportion of adults In Indiana who are obese Is greater than the national proportion. ' ' - . r I. . -. - S 1 To determine the Impact of variations In price on sales the t of Big Bob's Burger Barn sets different ' .. prices in Its burger joints In 75 stores located in different cities 3 Using the sales and price data, a simple regression is run with sales [in thousands of dollars) as the depenth 284 variable and price [In dollars) as the Independent variable 2 S 5 Use the following calculations and the accompanying regression summary output to answer questions 23:33]. E 2 7 zxy = 32903.44 )7 = 5.5312 :58 2x3 = 2444.551 ,7 = 77.5773 289 n = 75 290 291 DEPENDENT VARIABLE= SALE 292 Regrem Samoa 293 Multiple R A B C D E F G H K L M N P Q R S 291 DEPENDENT VARIABLE = SALES 292 Regression Statistics 293 Multiple R 294 R Square 295 Adjusted R Square 0.4237 296 Standard Error 297 Observations 75 298 299 ANOVA 300 df SS MS F Stat P-value 301 Regression 55.415691 1.55E-10 302 Residual 303 Total 3643.8515 304 305 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 306 Intercept 6.2133 19.9094 3.198E-31 111.3198 136.0859 307 PRICE 1.55E-10 808 309 23 The numerator of the formula to find the slope coefficient in the regression equation is 310 -179.453 311 b -186.631 312 C -194.096 313 d -201.860