Answer:
Step-by-step explanation:
The null hypothesis is:
H0: μ(1995)=μ(2019)
The alternative hypothesis is:
H1: μ(1995)<μ(2019)
Because Roger wants to know if mean weight of 16-old males in 2019 is more than the mean weight of 16-old males in 1995 the test only uses one tail of the z-distribution. It is not a two-sided test because in that case the alternative hypothesis would be: μ(1995)≠μ(2019).
To know the p-value, we use the z-statistic, in this case 1.89 and the significance level. Because the problem does not specify it, we will search for the p-value at a 5% significance level and at a 1%.
For a z of 1.89 and 5% significance level, the p-value is: 0.9744
For a z of 1.89 and 1% significance level, the p-value is: 0.9719
Answer:
C. p -> q
Step-by-step explanation:
Just did this on Edge2020. Hope this helps :)
Answer: Conditional frequencies enables users to get more specific information when analyzing a dataset.
Step-by-step explanation: Frequency refers to the count of occurrence of a particular variable.
Relative frequency is obtained by taking the ratio of the counts a particular variable and the total counts and of all available variables in the experiment or data.
Conditional Frequency allows us to input additional constraints to our frequency counts, especially in a two-way table. Enabling us to get more specific information by using conditional statements.
Answer:
Step-by-step explanation:
I would begin by distributing the L. It will be easier in the end to do it this way. There are a couple of ways you can do this, but distribution is the easiest. After you distribute the L you have
T = 2L + LRS
Next subtract the 2L to get
T - 2L = LRS. Lastly, to isolate the R, divide away the LS to get
= R In that second term, the L's cancel each other out, leaving us with
= R
