First we need to write the null and alternate hypothesis for this case.
Let x be the average number of text message sent. Then
Null hypothesis: x = 100
Alternate hypothesis: x > 100
The p value is 0.0853
If p value > significance level, then the null hypothesis is not rejected. If p value < significance level, then the null hypothesis is rejected.
If significance level is 10%(0.10), the p value will be less than 0.10 and we reject the null hypothesis and CAN conclude that:
The mean number of text messages sent yesterday was greater than 100.
If significance level is 5%(0.05), the p value will be greater than 0.05 and we cannot reject the null hypothesis and CANNOT conclude that:
The mean number of text messages sent yesterday was greater than 100.
Extra 10, 10 is half of what she ordered so she received an extra 50%
Answer:
I just learned this about a few weeks ago I hope this helps.
Step-by-step explanation:
Since it's cosine you're only looking at Adjacent and the hypotenuse which the adj is 20 and the hyp is 25 so since cosine is adj/hyp you do 20/25 then simplify it to 20/25 divide both by 5 so it's simplified to 4/5.
Then you do Cos-1(4/5)=36.869 which is rounded to the tenth 36.9 but rounded to the hundredth 36.87.
Hope this helps
Answer:
Part 1) The explanatory variable is the type of oven
It is a categorical variable
Part 2) The response variable is the baking time
It is a quantitative variable
part 3) two-sample z-test for proportions should be used for the test
Step-by-step explanation:
An explanatory variable is an independent variable that is not affected by all other variables. In this experiment, the type of oven is the input variable and it is not affected by any other variable
A categorical variable is one that has two or more categories without any intrinsic ordering of the categories. The type of oven is either gas or electric, so it is categorical.
A response variable is a dependent variable whose variation depends on other variables. The baking time in this experiment depends on the type of oven used
A quantitative variable is one that take on numerical values.
A two proportion z-test allows you to compare two proportions to see if they are the same. The null hypothesis (H0) for the test is that the proportions are the same. The alternate hypothesis (H1) is that the proportions are not the same.
