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katrin [286]
3 years ago
6

Suppose IQ scores were obtained for 20 randomly selected sets of couples. The 20 pairs of measurements yield x overbarequals100.

39​, y overbarequals103.6​, requals0.925​, ​P-valueequals​0.000, and ModifyingAbove y with caret equals negative 3.34 plus 1.07 x​, where x represents the IQ score of the husband. Find the best predicted value of ModifyingAbove y with caret given that the husband has an IQ of 91​? Use a significance level of 0.05.
Mathematics
1 answer:
LenaWriter [7]3 years ago
8 0

Answer:

\hat y = -3.34+ 1.07(91) = 94.03

Step-by-step explanation:

Data given

n=20 represent the sampel size

\bar X = 100.39 represent the sample mean for the independent variable (IQ score of the husband)

\bar y = 103.6 represent the sample mean for the dependent variable.

r =0.925 represent the correlation coefficient

Solution to the problem

The general expression for a linear model is given by:

y = \beta_0 + \beta_1 x

Where \beta_0 is the intercept and \beta_1 the slope

For this case we have a linear model given by the following expression:

\hat y = -3.34 +1.07 x

Where -3.34 is the intercept and 1.07 the slope. In order to find the best predicted value when X = 91 we just need to replace into the equation the value of 91 and we got this:

\hat y = -3.34+ 1.07(91) = 94.03

On this case is the best predicted value because E(\hat y) = y we have an unbiased estimator.

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14.3p – 32.24 = 127.92 14.3p – 32.24 + 32.24 = 127.92 + 32.24 14.3p = 160.16 StartFraction 14.3 p Over 14.3 EndFraction equals S
DiKsa [7]

Answer:

p = 11.2

Step-by-step explanation:

The computation is shown below:

Data provided in the question

2.6(5.5p – 12.4) = 127.92

Now

Distributive Propertyis

14.3p - 32.24 = 127.92

Addition Property is

14.3p = 127.92 + 32.24

Division Property is

14.3p ÷ 14.3 = 160.16 ÷ 14.3

p = 11.2

We simply find the value of p by applying the distributive property, addition property, and the division property and the same is to be considered

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Step-by-step explanation:

36x+72xy+27xy

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