If the amount of time taken to go said distance is x and the amount of time taken to go back said distance is y, then the amount of miles total is 7x+3y due to that for every hour, she adds 7 miles when going there and 3 miles for walking back. In addition, since the total amount of time is 4 hours, x+y=4 as the total time spent as well as 7x=3y due to that they're the same distance.
x+y=4
7x=3y
Dividing the second equation by 7, we get x=3y/7. Plugging that into the first equation, we get 3y/7+y=4=10y/7 (since y=7y/7). Multiplying both sides by 7 and then dividing both by 10, we get 28/10=2.8=y in hours. Since 0.1 hours is 60/10=6 minutes, and 0.8/0.1=8, 6*8=48 minutes=0.8 hours, meaning that she should plan to spend 2 hours and 48 minutes walking back
CL.1.142):
A):
x5 ==> 4 boxes = 3ft <==== x5
20 boxes = ? ft
20 boxes is 15 ft. high
B): x3 ===> 4 boxes = 3ft. <==== x3
? boxes = 9ft.
12 boxes will fit in one stack.
c): CL.143
Perimeter = 15 + 29 + 9 + 11 + 6 + 18 =====> 88m
A1 = b * h
(18)(15)
270m^2
A2 = b * h
(11)(9)
99
Total Area ======> 270 + 99 ======> 369m^2
CL.1-144
1/4 + 1/4 + 1/5 = 5/20 + 5/20 + 4/20 ====> 14/20
1/4 * 5/5 =====> 5/20
1/5 * 4/4 =====> 4/20
14/20 + ?/20 = 20/20
? = 6 Missing Section
6/20 ======> 3/10
CL-1.145
A): 40/100 = 4/10 ====> 2/5
0.4 ========> 40%
B): 1/6 ======> .00000
0.16 (Repeating 6) ======> 16.6%
C): 37.5/100 = 375/1000 =======> 3/8
0.375 =========> 37.5%
CL-1.146
ADD: 1/6 + 1/2 show all steps:
1/6 + 1/2
1/6 + 3/6
1 + 3 / 6
4/6 =======> 2/3 =======> Decimal: =======> 0.666667
Hope that helps!!!! : )
When we reject the null and the null is true, we have a made a type I error
The null hypothesis in statistics states that there is no difference between groups or no relationship between variables. It is one of two mutually exclusive hypotheses about a population in a hypothesis test.
null hypothesis is denoted as H₀
Reject the null hypothesis when the p-value is less than or equal to your significance level. Your sample data favor the alternative hypothesis, which suggests that the effect exists in the population. When you can reject the null hypothesis, your results are statistically significant.
when the p-value is greater than your significance level, you fail to reject the null hypothesis.
Sometimes , we reject our null hypothesis even when its true
there we made a type I error in hypothesis
To know more about null hypothesis here
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6 1/2% as a decimal is 6.05. 6 is a whole number, and 1/2% is 0.05 in decimal form.
I believe the answer is 2
