https://drive.google.com/file/d/15N-vqmYQwEQRvV04lyzvqGYIRh7mDqpb/view?usp=shari

Question

https://drive.google.com/file/d/15N-vqmYQwEQRvV04lyzvqGYIRh7mDqpb/view?usp=sharing

1. For AC and PP in the 2017 stats, perform the following computations Find the mean, median, mode, and standard deviation s of this sample. Create a histogram using your frequency table Draw a boxplot of the assembly costs Use the results from part (a) to find what percentage of the 36 days, AC is within ±1 of the mean. (Hint: Assume this sample was NOT taken from a Bell curve.) If 35.4% or more is considered a good percentage of profit, what proportion of the 36 days, PP are 35.4% or more? Of those days with PP of 35.4% or more, what percentage of those days were accomplished with an assembly cost of $330 or less? a. b. c. d. e. f. 2. Assuming that the mean AC for the first 36 months is normally distributed, do the following Find the mean and the standard deviation , then find what proportion of AC was between S320 and $350 per month Use the 36 months of statistics to create a scatterplot, with AC on the x-axis and PP on the y-axis. Draw in a trend line and calculate the equation for the line of regression. Using this equation from part c), approximate to the nearest whole number the percent of profit that could result from requiring an average assembly cost of $340 during the 36 months. Also approximate to the nearest cent the assembly cost that would result in producing an average of 34.7% per month during that same 36 months Using R, show that the data you used to establish your sample of sample means for the first semester is normally distributed by creating a Normal Quantile Plot (qqnorm) a. b. c. d. e. 3. Assuming that the 36 days in 2017 are a representative sample and that the 36 days' AC fit a Normal Distribution Curve, do an estimation of the Mean by establishing a margin of error and a confidence interval of the mean assembly cost recorded during the 36 days. Use a 95% confidence-level 4. For the 36 months from 2014-2016, you calculated the mean monthly AC for the company as well as the standard deviation. Use these as the basis for the mean hypothesis claim, Ho. a) Has this changed during the 36 days at the start of 2017? b) State your Alternative Hypothesis. c) Use a significance level of = 0.05 to find a Z-test and a P-value that either supports or rejects the null hypothesis Using the sample of the 36 days in 2017 for the company's AC, has there been a significant statistical change in the mean AC since 2014? State your conclusion in one descriptive sentence d)

Explanation / Answer

Question 4

Part a

The mean for AC for 36 days at the start of 2017 is given as 335.625.

The mean for previous data for AC for last three years is given as 328.7014.

This means, it has changed during the 36 days at the start of 2017.

Part b

The null and alternative hypothesis is given as below:

Null hypothesis: H0: The mean AC is 328.70.

Alternative hypothesis: Ha: The mean AC is not 328.70.

H0: µ = 328.70 versus Ha: µ 328.70

Part c

Here, we have to use one sample z test.

H0: µ = 328.70 versus Ha: µ 328.70

We are given

= 0.05

Xbar = 335.625

= 22.04782

n = 36

Test statistic = Z = (Xbar - µ) / [ / sqrt(n)]

Z = (335.625 – 328.70) / [22.04782/sqrt(36)]

Z = (335.625 – 328.70) /3.6746

Z = 1.8845

Lower critical value = -1.96

Upper critical value = 1.96

P-value = 0.0595

P-value > = 0.05

So, we do not reject the null hypothesis that mean AC is 328.70.

There is insufficient evidence to conclude that mean AC has changed.

Part d

Using the sample of the 36 days in 2017 for the company’s AC, there has not been a significant statistical change in the mean AC since 2014; because we get P-value greater than alpha value and we do not reject the null hypothesis that there is no any statistically significant change occurred in the mean AC.

Related Questions

Navigate

• Browse (All)
• Browse H
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.