The regression equation for the data given is y= -8.57 -2.31x
Step-by-step explanation:
The first step is to form a table as shown below;
x y xy x² y²
1 4 4 1 16
2 1 2 4 1
3 5 15 9 25
4 10 40 16 100
5 16 80 25 256
6 19 114 36 361
7 15 105 49 225
28 60 360 140 984 ------sum
A linear regression equation is in the form of y=A+Bx
where ;
x=independent variable
y=dependent variable
n=sample size/number of data points
A and B are constants that describe the y-intercept and the slope of the line
Calculating the constants;
A=(∑y)(∑x²) - (∑x)(∑xy) / n(∑x²) - (∑x)²
A=(60)(140) - (28)(360) / 7(140)-(28)²
A=8400 - 10080 /980-784
A= -1680/196
A= - 8.57
B= n(∑xy) - (∑x) (∑y) / n(∑x²) - (∑x)²
B= 7(360)-(28)(60) / 7(60) - (28)²
B=2520 - 1680 /420-784
B=840/-364
B= -2.31
y=A+Bx
y= -8.57 -2.31x
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Regression equation :brainly.com/question/12280902
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Answer:
Step-by-step explanation:
We want to determine a 95% confidence interval for the mean total cholesterol level of all males.
Number of sample, n = 355
Mean, u = 185 mg
Standard deviation, s = 16
For a confidence level of 95%, the corresponding z value is 1.96. This is determined from the normal distribution table.
We will apply the formula
Confidence interval
= mean +/- z ×standard deviation/√n
It becomes
185 +/- 1.96 × 16/√355
= 185 +/- 1.96 × 0.849
= 185 +/- 1.66404
The lower end of the confidence interval is 185 - 1.66404 =183.336
The upper end of the confidence interval is 185 + 1.66404 = 186.66
Therefore, with 95% confidence interval, the mean total cholesterol level of all males is between 183.336 mg and 186.66 mg
Answer:
14 maybe
Step-by-step explanation: