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Here is a graph with the equation you gave graphed on it.
The associative property states that we can regroup the terms of an expression and obtain the same result.
We have then:
The expression that complies with this property is given by:
Answer:
An equation that shows an example of the associative property of addition is:
a. (- 4 + i) + 4i = -4 + (i + 4i)
3)
Assuming that the population of the study has a normal distribution and that you are studying the population mean μ.
The statistic hypotheses are
If you look at the alternative hypotheses, it includes the symbol "<", which indicates that the test is <em>one-tailed</em>. This means that you will reject the null hypotheses at small values of the test statistic.
Since the sample size is small (n=4) and the given sample data. The test statistic to use for the test is the Student's t:
To calculate the value of the statistic under the null hypothesis you have to use the sample data and the value of the population mean under the null hypothesis:
μ= 87.8
sample mean= 75
sample standard deviation= 17.1
n=4
The test statistic under the null hypothesis is -1.497
The p-value is the probability corresponding to the calculated statistic if possible under the null hypothesis.
So you have to calculate the probability of obtaining the value t=-1497
The student t has n-1 degrees of freedom, since the sample taken is n=4, the degree of freedom is 3.
The p-value is then the accumulated probability up to -1.497 under a t-distribution with 3 degrees of freedom:
The p-value is equal to 0.1157
4)
To make a decision using the p-value, you have to compare the said value with the level of significance, following the decision rule:
- If the p-value ≥ α, do not reject the null hypothesis.
- If the p-value < α, reject the null hypothesis.
The p-value (0.1157) is greater than the significance level (α= 0.05)
The decision is "do not reject the null hypothesis."
