Answer:
67.5°, 107.5°
Step-by-step explanation:
For supplementary angles, their sum equals 180°.
Let x be the first angle and y be the second angle, then
x + y = 180°.
It is given that x = y + 45°.
So x + y = 180°
substituting x into the equation, we have
y + 45° + y = 180°
simplifying, we have
2y + 45° = 180°
collecting like terms, we have
2y = 180° - 45°
2y = 135°
dividing through by 2, we have
y = 135°/2
y = 67.5°
Since y = 67.5°
then x = y + 45°
x = 67.5° + 45°
x = 107.5°
The measures of the supplementary angles that satisfy the given conditions are 67.5° and 112.5°.
Let's say the measure of the second angle is x. Since the measure of the first angle is 45° more than the measure of the second, we can express the first angle as the measure of x + 45°.
By the definition of supplementary angles, we know that the sum of the measures of two supplementary angles is 180°. Therefore, we can create the following equation: x + (x + 45) = 180.
Solving this equation gives us:
So, "the second angle measures 67.5°, and the first angle, being x + 45°, measures 112.5°".
#SPJ12
Answer:
Step-by-step explanation:
Given that an ANOVA procedure is used for data obtained from four populations. Four samples, each comprised of 30 observations, were taken from the four populations.
Hence total observations are 30*4 =120
No of groups = 3
Hence numerator df = 3-1 =2
Now total degrees of freedom = 120-1 =119
So denominator degrees of freedom = 119-2 = 117
Thus F statistic will have numerator as 2 degrees of freedom and denominator as 117 degrees of freedom.
n1=120 n2=100
x1=4.1 minutes x2=3.4 minutes
σ1=2.2minutes σ2= 1.5 minutes
Test at the 0.05 level of significance to determinewhether the population mean checkout times of the two newsystems differ. Which system is preferred?
Answer:
We conclude that the population means checkout times of the two new systems differ.
Step-by-step explanation:
We are given the result in the following summary of the data;
System System B
n1=120 n2=100
x1=4.1 min x2=3.4 min
σ1=2.2 min σ2= 1.5 min
Let = population mean checkout time of the first new system
= population mean checkout time of the second new system
So, Null Hypothesis, : {means that the population mean checkout times of the two new systems are equal}
Alternate Hypothesis, : {means that the population mean checkout times of the two new systems differ}
The test statistics that will be used here is Two-sample z-test statistics because we know about population standard deviations;
T.S. = ~ N(0,1)
where, = sample mean checkout time of the first new systems = 4.1 min
= sample mean checkout time of the second new systems = 3.4 min
= population standard deviation of the first new systems = 2.2 min
= population standard deviation of the second new systems = 1.5 min
= sample of the first new systems = 120
= sample of the second new systems = 100
So, the test statistics =
= 2.792
The value of z-test statistics is 2.792.
Now, at 0.05 level of significance, the z table gives a critical value of -1.96 and 1.96 for the two-tailed test.
Since the value of our test statistics does not lie within the range of critical values of z, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region.
Therefore, we conclude that the population mean checkout times of the two new systems differ.
Answer:
1/2 or 0.5
Step-by-step explanation:
Answer:
12.5
Step-by-step explanation:
If the number of workers injured in each accident is independent of the number of accidents that occur, then the expected number of workers injured in a week equals the expected number of accidents per week times the expected number of workers injured in each accident.
But the expected number of workers injured in each accident is precisely the average or mean, so
Expected number of workers injured in a week = 5*2.5 = 12.5.
Or in other words, in 10 weeks there will probably be 125 workers injured.
The expected number of workers injured in a week at the industrial plant is 12.5, calculated by multiplying the expected number of accidents per week (5) by the expected number of workers injured per accident (2.5).
The expected number of accidents at an industrial plant per week is given as 5 and the mean number of workers injured per accident is given as 2.5. As the number of workers injured per accident is stated to be independent from the number of accidents that occur, we can merely multiply the two expected values to find the overall expected value of workers injured in a week.
So, Expected number of workers injured per week = Expected number of accidents per week * Expected number of workers injured per accident = 5 * 2.5 = 12.5.
This implies that, on average, we can expect 12.5 workers to be injured at the industrial plant per week.
#SPJ3
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exex fxf
Answer:
i know its a bit late but the answer below
Step-by-step explanation:
e/f
Answer:
1 ft. = 16 in.
Step-by-step explanation:
6 ft. 8 in. is 80 in.
then you would divide 80 by 5 to get 16.
not sure what scale factor you were looking for, so i did ft. to in.
not 100% sure though
best of luck!