Which description best describes the value of r = 0.86? O a moderate, negative linear relationship O a weak linear relationship O the strength of the relationship between the explanatory and the response variab O a strong, positive linear relationship 86% chance of the regression line being a good fit
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- For linear regression with one variable, the unpredicted portion of the Y-score variance (MS residual) has df = n - 2. True False Submit AnswerWhich description best describes the value of r = -.56? the strength of the relationship between the explanatory and the response variable 56% chance of the regression line being a good fit a moderate, negative linear relationship a strong, positive linear relationship a weak linear relationshipFind the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.7 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) Click the icon to view the critical values of the Pearson correlation coefficient r. F n example Get more help. The regression equation is y=-159.5+ 43.2 x (Round to one decimal place as needed.) 3 # The best predicted weight for an overhead width of 1.7 cm is kg. (Round to one decimal place as needed.) I 80 E 26 D 7.8 161 C $ 4 Q F4 8.3 212 R F Stv 9.9 276 07 20 V F5 T 9.1 215 G 6 B 9.7 262 746 MacBook Air FO 7.3 166 Y H & 7 N F7 U X +00 8 J DII FB - M ( 9 K O < I ) O |qqqqqqqqi L F10 Clear all P . V : ; F11 { + [ command option Check answer = ? 11 I F12 1
- If a researcher wants to predict an exam score given someone's SAT score, which test would be most appropriate? Group of answer choices Point biserial correlation Pearson's r correlation Independent samples t-test Simple regressionul Sprint 11:42 AM 86% Done Attachment 8 Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary. 1 3 5 7 9 9) y| 143 116 100 98 90 9) A) y = -150.7 + 6.8x B) y = -140.4 + 6.2x C) y = 140.4 – 6.2x D) y = 150.7 – 6.8xFill in the blanks. a. Positive correlations between observations of the response variable result in an underestimate of ________. b. Data collected from a designed experiment is generally preferable to data obtained from ________. c. Adata point whose removal has a substantial effect on one or more sample regression coefficients is called an _________.
- When there are omitted variables in your regression, then... Group of answer choices This has no effect on the estimation of the explanatory variable because the variable is omitted This will always bias the OLS estimation of the explanatory variable the estimation of the explanatory variable(s) is unaffected The OLS estimation is biased if the omitted variables are correlated with the included variablePrev The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the number of bids an Item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 28 33 36 42 45 Number of Bids 1 7 8 9 10 Step 3 of 6: Find the estimated value of y when x = 33. Round your answer to three decimal places. Table Copy Data NextThe data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $6 million. Is the result close to the actual number of viewers, 8.9 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. 98 3.5 3 7 13 12 13 10 2 6.8 6.3 10.2 8.5 4.4 1.8 2.7 What is the regression equation? y=+x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $6 million? The best predicted number of viewers for a television star with a salary of $6 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 8.9 million? O A. The result is very close to the actual number of viewers of 8.9 million. O B. The…
- Which of the following determines the direction of the regression line? Group of answer choices intercept slope predicted score criterion scoreLINEAR CORRELATION PROJECT / Topic: Does per capita income affect birth rates I need help with the trendline, the hypothesis, and conclusion, any confounding variables there might be and the r- value, and compare the r-value to the appropriate cutoff value, with correct interpretation. (remember for a sample size of 20, the absolute value of r should be greater than 0.45) The regression equation is: y=21.129−0.108xwhere y: average birth rate and x: per capita incomey and x is negatively related i.e with increase in x , y decreses and vice versa ((* for a sample size of 20, the absolute value of r should be greater than 0.45)) Country Per Capita Income Average Birth Rate Afghanistan $ 530 37.9 Austria $ 51,460 9.5 Cambodia $ 1,530 23 Canada $ 46,370 10.3 Denmark $ 63,950 10.5 Ecuador $ 6,090 17.9 Ethiopia $…Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next