Answer:
Missing Number) 55
Property being used) Distributive
Step-by-step explanation:
To find the missing number, just plug in reasonable numbers from the other equation. It is distributive because the 55 is being distributed into everything that is inside the parentheses. If you need more help, comment and I'll be more than glad to assist you! :P
Answer:
25.12
Step-by-step explanation:
round pi to first 2 digits after decimal point.
3.14 x 8 =25.12
In statistics, a Chi-squared test may be used to determine holiday choice and gender and α (alpha) is the response variable.
<h3>What is the Chi-squared test? </h3>
A statistical technique called the chi-square test is used to compare actual outcomes with predictions.
The goal of this test is to establish if a discrepancy between actual and predicted data is the result of chance or a correlation between the variables you are researching.
Whether there is a statistically significant association between categorical variables is determined by the Chi-square test of independence.
This issue is addressed by a hypothesis test. The chi-square test of association is another name for this assessment.
Hence,in stats would a test looking at gender & holiday preference yes you can do a Chi-squared test and α(alpha) is the response variable.
To learn more about the Chi-squared test refer;
brainly.com/question/14082240
#SPJ1
Answer:
angle 3 = angle 7 = 114° ------- because corresponding angles are equal
Answer:
Step-by-step explanation:
1) As the sample size is 1,000 and there are 23 defectives in the output of the sample collected from Machine #1, the answer is 23/1000=0.023.
2) Estimate of the process proportion of defectives is the average of the proportion of defectives from all samples. In this case, it is : (23+15+29+13)/{4*(1000)}=80/4000=0.02.
3) Estimate of the Standard Deviation: Let us denote the mean (average) of the proportion of defectives by p. Then, the estimate for the standard deviation is : sqrt{p*(1 - p)/n}. Where n is the sample size. Putting p = 0.02, and n = 1000, we get: σ=0.0044.
4) The control Limits for this case, at Alpha risk of 0.05 (i.e. equivalent to 95% confidence interval), can be found out using the formulas given below:
Lower Control Limit : p - (1.96)*σ = 0.02 - (1.96)*0.0044=0.0113.
& Upper Control Limit: p + (1.96)*σ = 0.02 + (1.96)*0.0044 = 0.0287.
5) The proportion defective in each case is : Machine #1: 0.023; Machine #2: 0.015; Machine# 3: 0.029; Machine# 4: 0.013. For the Lower & Upper control limits of 0.014 & 0.026; It is easy to see that Machines #3 & #4 appear to be out of control.
