Answer:
The <em>p</em>-value of the test is 0.0512.
Step-by-step explanation:
The <em>p</em>-value of a test is well-defined as per the probability, [under the null hypothesis (H₀)], of attaining a result equivalent to or more extreme than what was the truly observed value of the test statistic.
In this case the output of the t-test_ind method from scipy module is provided as follows:
Output = (-1.99, 0.0512)
The first value within the parentheses is the test statistic value.
So the test statistic value is, -1.99.
And the second value within the parentheses is the <em>p</em>-value of the test.
So the <em>p</em>-value of the test is 0.0512.
Answer:
<em>A: For each increase in the number of procrastination days by 1, the predicted grade decreases by 3.64 points.</em>
Step-by-step explanation:
<u>The slope of a Regression Line</u>
A straight line can be represented in the slope-intercept form:
y = mx + b
Where m is the slope and b is the y-intercept.
The slope describes how fast and in what direction the graph goes when x changes values.
If m is positive, increments in x imply increments in y.
If m is negative, increments in x imply decrements in y.
The regression line is:
ŷ = –3.64x + 96.5
Where:
x = the number of procrastination days
ŷ = the predicted grade
We can say the slope is m=-3.64. This means that:
A: For each increase in the number of procrastination days by 1, the predicted grade decreases by 3.64 points.
Answer: This is what Khan Academy said the answer was
I think that it's TRUE because it is in the middle when you draw the segment out
