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8.93. A correlation coefficient based on a sample of size 27 was computed to be 0.40. Can we conclude at a significance level of (a) 0.05, (b) 0.01, that the corresponding population correlation coefficient is significantly greater than zero 8.94. A correlation coefficient based on a sample of size 35 was computed to be 0.50. Can we reject the hypothesis that the population correlation coefficient is (a) as small as r 0.30, (b) as large as r 0.70, using a 0.05 significance level 8.95. Find (a) 95%, (b) 99%, confidence limits for a correlation coefficient that is computed to be 0.60 from a sample of size 28.

8.96. Work Problem 8.95 if the sample size is 52. 8.97. Find 95% confidence limits for the correlation coefficient computed in Problem 8.76.

CHAP. 4]

8.98. Two correlation coefficients obtained from samples of sizes 23 and 28 were computed to be 0.80 and 0.95, respectively. Can we conclude at a level of (a) 0.05, (b) 0.01, that there is a significant difference between the two coefficients

RB I1 RB RC RD I2 R D I3 0 RD I2 RD RE I3 Vb Placing the equations in matrix form, 2 RA RB 4 RB 0 32 3 2 3 0 Va I1 RD 54 I2 5 4 0 5 Vb RD RE I3

8.99. The sample least-squares regression lines for a set of data involving X and Y are given by 2x 5x 8y 2. Find the linear correlation coefficient. 5y 3,

Fig. 12-3

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8.100. Find the correlation coefficient between the heights and weights of 300 adult males in the United States as given in the Table 8-41. Table 8-41 HEIGHTS x (inches) 59 62 90 109 WEIGHTS y (pounds) 110 129 130 149 150 169 170 189 190 209 210 229 2 7 5 2 63 66 1 8 15 12 7 2 4 22 63 28 10 1 2 7 19 32 20 4 1 5 12 7 2 67 70 71 74 75 78

Fig. 4-3 The elements of the matrices can be indicated 2 R11 4 R21 R31 in general form as follows: 32 3 2 3 V1 R12 R13 I1 R22 R23 54 I2 5 4 V2 5 R32 R33 I3 V3

8.101. (a) Find the least-squares regression line of y on x for the data of Problem 8.100. (b) Estimate the weights of two men whose heights are 64 and 72 inches, respectively. 8.102. Find (a) sy.x, (b) sx.y for the data of Problem 8.100. 8.103. Find 95% confidence limits for the correlation coefficient computed in Problem 8.100. 8.104. Find the correlation coefficient between U.S. consumer price indexes and wholesale price indexes for all commodities as shown in Table 8-42. The base period 1947 1949 100. Table 8-42 Year Consumer Price Index Wholesale Price Index 1949 101.8 99.2 1950 102.8 103.1 1951 111.0 114.8 1952 113.5 111.6 1953 114.4 110.1 1954 114.8 110.3 1955 114.5 110.7 1956 116.2 114.3 1957 120.2 117.6 1958 123.5 119.2

Now element R11 (row 1, column 1) is the sum of all resistances through which mesh current I1 passes In Fig 4-3, this is RA RB Similarly, elements R22 and R33 are the sums of all resistances through which I2 and I3 , respectively, pass Element R12 (row 1, column 2) is the sum of all resistances through which mesh currents I1 and I2 pass The sign of R12 is if the two currents are in the same direction through each resistance, and if they are in opposite directions In Fig 4-3, RB is the only resistance common to I1 and I2 ; and the current directions are opposite in RB , so that the sign is negative.

8.105. Refer to Table 8-43. (a) Graph the data. (b) Find a least-squares line fitting the data and construct its graph. (c) Compute the trend values and compare with the actual values. (d) Predict the price index for medical care during 1958 and compare with the true value (144.4). (e) In what year can we expect the index of medical costs to be double that of 1947 through 1949, assuming present trends continue

Table 8-43

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