(0.9)* (1.5+5.8)
First, Add the values to the right. You get (0.9) * (7.3)
Multiply 9 and 73 to get 730 -73, which is 700-43, 660 - 3, which is 657.
Divide by 100 by moving the decimal point to get 6.57 as your final answer.
Hope that helped!
The answer is D because the two points are in x-value -1 and 3
( a ) The null hypothesis, represented by 
, should be equivalent to 0.6 pounds per square inch, considering it normally is predicted to be equivalent to the population parameter, which, in this case, is 0.6 psi ( pounds per square inch. ) The alternative hypothesis on the other hand contradicts the null hypothesis, and as the manager feels the pressure has been reduced, the alternative hypothesis points that the pressure is less than 0.6 psi -
<em>stigma is represented by the sign ( σ )</em>
( b ) Now if you were to reject the null hypothesis when true, that would lead to a type I error. That would mean that to reject the fact that σ = 0.7, and accept that σ < 0.7, even though σ = 0.7 is true, would make a type I error.
_______
( c ) A type II error is quite the opposite. Accepting the null hypothesis while rejecting the alternative hypothesis would make a type II error.
Hello, I Am BrotherEye
Answer:
Median = 46.5
Minimum = 32
Maximum = 62
Lower quartile = 38
Upper quartile = 59
Step-by-step explanation:
Before we can proceed to solving any of these, it is best you arrange your data first from least to greatest
32 34 37 39 41 45 48 53 58 60 61 62
First we have the median. The Median is the middle value. In this case we an even number of data, which is 12 data points. The middle value of the data would be found in between the 6th and 7th data point:
45 and 48
To get the middle value, you need to solve for the value that is in the middle of 45 and 48 by getting the sum of both numbers and dividing it by two.
45 + 48 = 93
93 ÷ 2 = 46.5
The minimum and maximum value is merely the least and greatest number.
Here we have:
Minimum = 32
Maximum = 62
To get the lower and upper quartiles, just remember that quartiles divide the data into 4 equal parts. All you need to do is find the value that is in between each quarters of the data:
Q1 (Lower) Q2(Median) Q3(Upper)
32 34 37 | 39 41 45 | 48 53 58 | 60 61 62
Like the median, we will find the value that comes in between each quarter.
Q1
37 + 39 = 76
76 ÷ 2 = 38
Lower quartile = 38
Q3:
58 + 60 = 118
118 ÷ 2 = 59
Upper quartile = 59
