A) How many murders per 100,000 residents can be expected in a state with 10.7 thousand automatic weapons? B) How many murders per 100,000 residents can be expected in a state with 2.1 thousand automatic weapons
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The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states.
| xx | 11.7 | 8.4 | 6.6 | 3.9 | 2.4 | 2.4 | 2.2 | 0.6 |
|---|---|---|---|---|---|---|---|---|
| yy | 14 | 10.9 | 9.4 | 7.5 | 6 | 5.8 | 5.8 | 4.4 |
xx = thousands of automatic weapons
yy = murders per 100,000 residents
Use excel to determine the equation of the regression line. (Round to 2 decimal places)
Determine the regression equation in
y = b0 + bx(x) form and write it below.
A) How many murders per 100,000 residents can be expected in a state with 10.7 thousand automatic weapons?
B) How many murders per 100,000 residents can be expected in a state with 2.1 thousand automatic weapons?
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8 7.1 3.3 2.5 2.6 2.2 0.9 yy 14.3 10.5 10.4 6.7 6.1 6.2 6.1 4.7 xx = thousands of automatic weaponsyy = murders per 100,000 residents Use your calculator to determine the equation of the regression line. (Round to 2 decimal places)(A)Determine the regression equation in y = ax + b form and write it below?(B) How many murders per 100,000 residents can be expected in a state with 1.8 thousand automatic weapons? Answer = Round to 3 decimal places. (C) How many murders per 100,000 residents can be expected in a state with 6.5 thousand automatic weapons? Answer = Round to 3 decimal places.A statistics professor wants to determine how students' final grades are related to mid-term exam scores, applied in the middle of the term, and the number of classes missed. The teacher selects 10 students from his class and obtains the following data as an attachment. Y = b + m1x1 + m2x2 being the general form of the multiple regression equation referring to the data above. Check the alternative that corresponds to the approximate value of b, m1 and m2, respectively: a) 46,39; 0,54; -4,89 b) -4,89; 0,54; 46,39 c) 46,39; -4,89; 0,54 d) -4,89; 46,39; 0,54
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8 7.1 3.3 2.5 2.6 2.2 0.9 yy 14.3 10.5 10.4 6.7 6.1 6.2 6.1 4.7 xx = thousands of automatic weaponsyy = murders per 100,000 residents a) Use your calculator to determine the equation of the regression line. (Round to 2 decimal places)Determine the regression equation in y = ax + b form and write it below. ? B) How many murders per 100,000 residents can be expected in a state with 6.5 thousand automatic weapons ? Round to 3 decimal places.The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.4 8 7.2 3.3 2.3 2.6 2.4 0.4 yy 13.4 10.9 10.3 6.8 6 6.2 6.2 4.3 xx = thousands of automatic weaponsyy = murders per 100,000 residentsDetermine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 1.5 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 5.4 thousand automatic weapons? Answer = Round to 3 decimal places.The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.5 8.2 6.6 3.7 2.9 2.8 2.1 0.4 yy 13.6 11.2 9.3 7.2 6.7 6.4 6 4.3 xx = thousands of automatic weaponsyy = murders per 100,000 residents Use your calculator to determine the equation of the regression line. (Round to 2 decimal places)Determine the regression equation in y = ax + b form and write it below. A) How many murders per 100,000 residents can be expected in a state with 10.5 thousand automatic weapons?Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 10.8 thousand automatic weapons?Answer = Round to 3 decimal places.
- The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. a. Fit the regression line y = a+bx to the data and interpret the results. b. Use the regression equation to determine the SY16C grade for a college student who scored60 on their achievement test. What would their SY16C grade beThe table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8.3 7 3.8 2.6 2.6 2.7 0.9 yy 13.7 11.4 10 7.2 6.3 6 6.2 5.1 xx = thousands of automatic weaponsyy = murders per 100,000 residentsDetermine the regression equation in y = a + bx form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 2.4 thousand automatic weapons? Answer = Round to 4 decimal places. B) How many murders per 100,000 residents can be expected in a state with 2.3 thousand automatic weapons? Answer = Round to 4 decimal places.A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Consequently, the appraiser decided to fit the simple linear regression model: E(y) = β0 + β1x, where y = appraised value of the house (in thousands of dollars) and x = number of rooms. Using data collected for a sample of n = 74 houses in East Meadow, the following results were obtained: = 74.80 + 19.84 xGive a practical interpretation of the estimate of the slope of the least squares line. For a house with 0 rooms, we estimate the appraised value to be $74,800. For each additional room in the house, we estimate the appraised value to increase $74,800. For each additional room in the house, we estimate the appraised value to increase $19,840. For each additional dollar of…
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8.1 6.7 3.3 2.7 2.3 2.2 0.3 yy 13.8 10.7 9.9 6.6 6.1 5.9 6.1 4.5 xx = thousands of automatic weaponsyy = murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 6.4 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 6.7 thousand automatic weapons? Answer = Round to 3 decimal places.In a fisheries researcher's experiment, the correlation between the number of eggs in the nest and the number of viable (surviving) eggs for a sample of nests is r = 0.67. The equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y = 0.72x + 17.07. For a nest with 140 eggs, what is the predicted number of viable eggs?What is the effect of this violation on the regression model? "The number of observations n is less than or equal to the number of parameters to be estimated"
