1. The table shows a function.
1 answer:
Answer: a) Linear function
b) adding 8 each time x increases by 1
c) (0,13)
Step-by-step explanation:
For the given table, the rate of change is constant throughout the table.
The rate of change =
Similarly we can check for every interval, the rate of change remains constant .
Thus, it is a linear function and the pattern we observe here is "adding 8 each time x increases by 1".
We know that the ordered pair of y intercept = (0,y)
In the table at x=0, y=13
hence, the y intercept of the given function is (0,13)
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Answer:
The incentive program does not cuts down on the number of days missed by employees.
Step-by-step explanation:
The dependent t-test (also known as the paired t-test or paired samples t-test) compares the two means associated groups to conclude if there is a statistically significant difference amid these two means.
A paired <em>t</em>-test would be used to determine whether the incentive program cuts down on the number of days missed by employees.
The hypothesis for the test can be defined as follows:
<em>H₀</em>: The incentive program does not cuts down on the number of days missed by employees, i.e. <em>d</em> ≥ 0.
<em>Hₐ</em>: The incentive program cuts down on the number of days missed by employees, i.e. <em>d</em> < 0.
From the information provided the data computed is as follows:
Compute the test statistic value as follows:
The test statistic value is -1.16.
Decision rule:
If the p-value of the test is less than the significance level then the null hypothesis will be rejected and vice-versa.
Compute the p-value of the test as follows:
*Use a t-table.
The p-value of the test is 0.1379.
The p-value of the test is very large for all the commonly used significance level. The null hypothesis will not be rejected.
Thus, there is not enough evidence to support the claim.
Conclusion:
The incentive program does not cuts down on the number of days missed by employees
