The skewness of the plot is positive skewness, and the equation of the regression line is y = -0.052x + 2.706
The mean, standard deviation, min, max, etc.
To do this, we make use of the following data values
15, 16, 16, 17, 17, 17, 20, 22, 22, 30
The mean is calculated using:
Mean = Sum/Count
So, we have:
Mean = (15+ 16+ 16+ 17+ 17+ 17+ 20+ 22+ 22+30)/10
Evaluate
Mean = 19.2
Using a graphing calculator, we have:
Standard Deviation, σ = 4.30
The min and the max are:
Min = 15
Max = 30
See attachment for the histogram.
From the attached histogram, we can see that the skewness of the plot is positive skewness
The percentage area between min and max expenses.
The min and the max values are the range of the normal plot.
So, the percentage area between these values is 100%
Inspect three samples
Let the three samples be
16, 17, and 30
The sample mean is:
Mean = Sum/Count
So, we have:
Mean = (16 + 17 + 30)/3
Evaluate
Mean = 21
The sample mean is different from the population mean
Since the means are not equal, then we fail to accept the Null hypothesis.
The correlation coefficient
To do this, we make use of a graphing calculator with the following calculation summary:
X Values
- ∑ = 120
- Mean = 20
- ∑(X - Mx)2 = SSx = 154
Y Values
- ∑ = 10
- Mean = 1.667
- ∑(Y - My)2 = SSy = 3.333
X and Y Combined
- N = 6
- ∑(X - Mx)(Y - My) = -8
R Calculation
r = ∑((X - My)(Y - Mx)) / √((SSx)(SSy))
r = -8 / √((154)(3.333)) = -0.3531
The correlation coefficient -0.3531 means that there is a negative correlation between the data values
The equation of the Regression line
To do this, we make use of a graphing calculator with the following calculation summary:
- b = SP/SSX = -8/154 = -0.05195
- a = MY - bMX = 1.67 - (-0.05*20) = 2.70563
So, we have:
y = -0.052x + 2.706
Hence, the equation of the regression line is y = -0.052x + 2.706
See attachment 2 for the scatter plot.
Read more about scatter plots and histograms at:
https://brainly.com/question/6592115
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