There is 75% decrease.
Step-by-step explanation:
Given,
Old value = 688 qt
New value = 172 qt
Change = New value - Old value
Change = 172 - 688
Change = -516 qt
The negative sign indicates decrease.
Decrease percent =
Decrease percent =
Decrease percent =
Decrease percent = 75%
There is 75% decrease.
Keywords: division, subtraction
Learn more about subtraction at:
#LearnwithBrainly
The amount of each of the 6 payments will be $41.50
Step-by-step explanation:
Given,
Cost of bike including taxes = $349
Down payment = $100
Amount left to pay = Cost of bike - Down payment
Amount left to pay = 349 - 100
Amount left to pay = $249
She agrees to pay in 6 equal payments, therefore, we will divide the total amount to pay by 6.
Amount to pay for one month =
Amount to pay for one month =
The amount of each of the 6 payments will be $41.50
Keywords: division, subtraction
Learn more about subtraction at:
#LearnwithBrainly
Answer:
Step-by-step explanation:
Hello!
You need to test at 1% if the average highway gas mileage is the same for three types of vehicles (midsize cars, SUV's and pickup trucks) to compare the average values of the three groups altogether, you have to apply an ANOVA.
n | Mean | Std. Dev.
Midsize | 31 | 25.8 | 2.56
SUV’s | 31 | 22.68 | 3.67
Pickups | 14 | 21.29 | 2.76
Be the study variables :
X₁: highway gas mileage of a midsize car
X₂: highway gas mileage of an SUV
X₃: highway gas mileage of a pickup truck.
Assuming these variables have a normal distribution and are independent.
The hypotheses are:
H₀: μ₁ = μ₂ = μ₃
H₁: At least one of the population means is different.
α: 0.01
The statistic for this test is:
~
Attached you'll find an ANOVA table with all its components. As you see, to manually calculate the statistic you have to determine the Sum of Squares and the degrees of freedom for the treatments and the errors, next you calculate the means square for both and finally the test statistic.
<u>For the treatments:</u>
The degrees of freedom between treatments are k-1 (k represents the amount of treatments):
<u>The sum of squares is: </u>
SSTr: ∑ni(Ÿi - Ÿ..)²
Ÿi= sample mean of sample i ∀ i= 1,2,3
Ÿ..= grand mean, is the mean that results of all the groups together.
So the Sum of squares pf treatments SStr is the sum of the square of difference between the sample mean of each group and the grand mean.
To calculate the grand mean you can sum the means of each group and dive it by the number of groups:
Ÿ..= (Ÿ₁ + Ÿ₂ + Ÿ₃)/ 3 = (25.8+22.68+21.29)/3 = 23.256≅ 23.26
= (Ÿ₁ - Ÿ..)² + (Ÿ₂ - Ÿ..)² + (Ÿ₃ - Ÿ..)²= (25.8-23.26)² + (22.68-23.26)² + (21.29-23.26)²= 10.6689
<u>For the errors:</u>
The degrees of freedom for the errors are:
The Mean square are equal to the estimation of the variance of errors, you can calculate them using the following formula:
<u>Now you can calculate the test statistic</u>
The rejection region for this test is <em>always </em>one-tailed to the right, meaning that you'll reject the null hypothesis to big values of the statistic:
If ≥ 4.07, reject the null hypothesis.
If < 4.07, do not reject the null hypothesis.
Since the calculated value is less than the critical value, the decision is to not reject the null hypothesis.
Then at a 1% significance level you can conclude that the average highway mileage is the same for the three types of vehicles (mid size, SUV and pickup trucks)
I hope this helps!
