<span>The dimensions are 40 inches by 55 inches.
Explanation<span>:
We know that perimeter is the sum of all of the sides. Since this is rectangular, opposite sides are equal. This gives us
y+11/8y+y+11/8y=190.
Combining like terms, we have
2y+22/8y=190.
Writing 22/8 as a mixed number, we have
2y+2 3/4y=190
4 3/4y=190.
Divide both sides by 4 3/4:
(4 3/4y)</span></span>÷<span><span>(4 3/4)=190</span></span>÷<span><span>(4 3/4)
y=190</span></span>÷<span><span>(4 3/4).
Convert the mixed number to an improper fraction:
y=190</span></span>÷<span><span>(19/4).
To divide fractions, flip the second one and multiply:
y=190*(4/19)=760/19=40.
Since y=40, 11/8y=11/8(40)=440/8=55.</span></span>
Answer:
Conclusion
There is no sufficient evidence to conclude that the mean of the home prices from Ascension parish is higher than the EBR mean
Step-by-step explanation:
From the question we are told that
The population mean for EBR is 
The sample mean for Ascension parish is 
The p-value is 
The level of significance is 
The null hypothesis is 
The alternative hypothesis is 
Here
is the population mean for Ascension parish
From the data given values we see that

So we fail to reject the null hypothesis
So we conclude that there is no sufficient evidence to conclude that the mean of the home prices from Ascension parish is higher than the EBR mean

so, 13 of the 20 tables have 6 chairs each.
that means, the remaining 7 tables, have 4 chairs each.
13 * 6 = 78 chairs total for those 13 tables.
7 * 4 = 28 chairs total for the remaining 7 tables.
78 + 28, that's how many.
Answer: 2.1 Pull out like factors :
6s - 2r = -2 • (r - 3s)
Equation at the end of step
((0-(9•(6s-4r)))+3s)--14•(r-3s)
Pulling out like terms
4.1 Pull out like factors : 6s - 4r = -2 • (2r - 3s)
Equation at the end of step
((0--18•(2r-3s))+3s)--14•(r-3s)
Final result :
<u>50r - 93s</u>
Answer:
One-way ANOVA
Step-by-step explanation:
One-way ANOVA(analysis of variance) a testing method in statistics that is used to compare the means of two or more independent samples, to check if the differences are statistically significant.
In this case, we have three groups which their various reaction time to caffeine is to be tested using the same testing method (amount of caffeine). Hence the appropriate test to use here is the one-way ANOVA