55. Best Electronics Inc. offers a “no hassle” returns policy. The daily number of customers
returning items follows the normal distribution. The mean number of customers returning
items is 10.3 per day and the standard deviation is 2.25 per day.
a. For any day, what is the probability that eight or fewer customers returned items?
b. For any day, what is the probability that the number of customers returning items is
between 12 and 14?
c. Is there any chance of a day with no customer returns?

I need helping showing this and computing this in excel

Consider the two separate samples given in the data set (samplecomparison.xlsx). Answer the questions below. Data listed below.

The range of the first data set is _____ .

The variance of the first data set is ____ . (Round to three decimal places as needed)

The standard deviation of the first data set is _____ . (Round to three decimal places as needed)

The range of the second data set is _____ .

The variance of the second data set is _____ . (Round to three decimal places as needed)

The standard deviation of the second data set is _____ . (Round to three decimal places as needed)

Which data set is most spread out based on these statistics?

Now remove the largest number from each data set and repeat the calculations (samplecomparison.xlsx). Answer the questions below.

The range of the first data set is _____ .

The variance of the first data set is _____ . (Round to three decimal places as needed)

The standard deviation of the first data set is _____ . (Round to three decimal places as needed)

The range of the second data set is _____ .

The variance of the second data set is _____ . (Round to three decimal places as needed)

The standard deviation of the second data set is _____ . (Round to three decimal places as needed)

Compare the results of parts the last three parts. Which statistic seems to be the most affected by the outliers, in terms of change of whole number values?

a. The standard deviation.

b. The variance.

c. The range.

d. There is no difference between the two samples.

Sample comparison data:

On December 1st a company pays $1,380 to a catering company for the company Christmas party scheduled for mid December 2015. In recording this transaction the December 31st financial statements would reflect:

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Question 21 pts

Which of the following is a current asset?

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Question 31 pts

The net income from the bottom of the statement of income is connected to the statement of financial position (balance sheet) through which of the following accounts?

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Question 41 pts

Which of the following is an operating activity for a department store?

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Question 51 pts

If a company is at the end of its first year of operations, which of the following is/are true?

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Question 61 pts

A public company issues a share to Investor A in exchange for cash of $10. One year later the company's shares are trading on the stock exchange at a market price of $15 per share. Which of the following statements is true?

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Question 71 pts

The two primary sources of funds to finance a company's expansion are:

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Question 81 pts

A company collects cash from a customer that had purchased goods on account three months earlier. In recording the cash collection there would be

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Question 91 pts

Which of the following best describes an asset?

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Question 101 pts

Material information is information that would impact the decision of a financial statement user. Materiality is most closely related to:

How much variance in grades is explained by artistic sensitivity? Show how you derived your answer

Scoresby Inc. tracks the number of units purchased and sold throughout each year but applies its inventory costing method at the end of the year, as if it uses a periodic inventory system. Assume its accounting records provided the following information at the end of the annual accounting period, December 31.

A recent survey conducted by a foundation reported that 74​% of teens admitted to texting while driving. A random sample of 42 teens is selected. Use the normal approximation to the binomial distribution to answer parts a through e.

a. Calculate the mean and standard deviation for this distribution.

The mean is _________.

​(Round to four decimal places as​ needed.)

The standard deviation is ___________.

b. What is the probability that more than 36 of the 42 teens admit to texting while​ driving?

The probability is __________..

​(Round to four decimal places as​ needed.)

c. What is the probability that exactly 24 of the 42 teens admit to texting while​ driving?

The probability is _____________.

​(Round to four decimal places as​ needed.)

d. What is the probability that 27​, 28​, or 29 of the 42 teens admit to texting while​ driving?

The probability is ___________.

​(Round to four decimal places as​ needed.)

e. What is the probability that fewer than 32 of the 42

teens admit to texting while​ driving?

The probability is ___________.

​(Round to four decimal places as​ needed.)

Scoresby Inc. tracks the number of units purchased and sold throughout each year but applies its inventory costing method at the end of the year, as if it uses a periodic inventory system. Assume its accounting records provided the following information at the end of the annual accounting period, December 31.

PrimeFlix sells one-year online subscriptions for viewing classic movies. Customers are required to pay for the subscription at the beginning of the subscription period. On April 1, 2021, total sales of one-year subscriptions are $12,000. What is the adjusted balance of Deferred Revenue on December 31, 2021?

• $9,000.

• $3,000.

• $0.

• $12,000.

Step 4:

What percent of the variation in corn yield is explained by these two variables? Give your answers to 2 decimal places and do not include units in your answers.

Percent explained by the model = %

Step 5:

Using the regression equation, find a point estimate for the corn yield for 2014 Assume that the soy bean yield for that year is 42.

Point Estimate = (Give your answer to 1 decimal place.)

ID      Year    CornYield       SoyBeanYield
1       1957    48.3    23.2
2       1958    52.8    24.2
3       1959    53.1    23.5
4       1960    54.7    23.5
5       1961    62.4    25.1
6       1962    64.7    24.2
7       1963    67.9    24.4
8       1964    62.9    22.8
9       1965    74.1    24.5
10      1966    73.1    25.4
11      1967    80.1    24.5
12      1968    79.5    26.7
13      1969    85.9    27.4
14      1970    72.4    26.7
15      1971    88.1    27.5
16      1972    97      27.8
17      1973    91.3    27.8
18      1974    71.9    23.7
19      1975    86.4    28.9
20      1976    88      26.1
21      1977    90.8    30.6
22      1978    101     29.4
23      1979    109.5   32.1
24      1980    91      26.5
25      1981    108.9   30.1
26      1982    113.2   31.5
27      1983    81.1    26.2
28      1984    106.7   28.1
29      1985    118     34.1
30      1986    119.4   33.3
31      1987    119.8   33.9
32      1988    84.6    27.0
33      1989    116.3   32.3
34      1990    118.5   34.1
35      1991    108.6   34.2
36      1992    131.5   37.6
37      1993    100.7   32.6
38      1994    138.6   41.4
39      1995    113.5   35.3
40      1996    127.1   37.6
41      1997    126.7   38.9
42      1998    134.4   38.9
43      1999    133.8   36.6
44      2000    136.9   38.1
45      2001    138.2   39.6
46      2002    129.3   38.0
47      2003    142.2   33.9
48      2004    160.3   42.2
49      2005    147.9   43.1
50      2006    149.1   42.9
51      2007    150.7   41.7
52      2008    153.9   39.7
53      2009    164.7   44.0
54      2010    152.8   43.5
55      2011    147.2   41.9
56      2012    123.4   39.8
57      2013    158.8   43.3

ID      Year    CornYield       SoyBeanYield
1       1957    48.3    23.2
2       1958    52.8    24.2
3       1959    53.1    23.5
4       1960    54.7    23.5
5       1961    62.4    25.1
6       1962    64.7    24.2
7       1963    67.9    24.4
8       1964    62.9    22.8
9       1965    74.1    24.5
10      1966    73.1    25.4
11      1967    80.1    24.5
12      1968    79.5    26.7
13      1969    85.9    27.4
14      1970    72.4    26.7
15      1971    88.1    27.5
16      1972    97      27.8
17      1973    91.3    27.8
18      1974    71.9    23.7
19      1975    86.4    28.9
20      1976    88      26.1
21      1977    90.8    30.6
22      1978    101     29.4

23      1979    109.5   32.1
24      1980    91      26.5
25      1981    108.9   30.1
26      1982    113.2   31.5

27      1983    81.1    26.2
28      1984    106.7   28.1
29      1985    118     34.1
30      1986    119.4   33.3
31      1987    119.8   33.9
32      1988    84.6    27.0
33      1989    116.3   32.3
34      1990    118.5   34.1
35      1991    108.6   34.2
36      1992    131.5   37.6
37      1993    100.7   32.6
38      1994    138.6   41.4
39      1995    113.5   35.3
40      1996    127.1   37.6
41      1997    126.7   38.9
42      1998    134.4   38.9
43      1999    133.8   36.6
44      2000    136.9   38.1
45      2001    138.2   39.6
46      2002    129.3   38.0
47      2003    142.2   33.9
48      2004    160.3   42.2
49      2005    147.9   43.1
50      2006    149.1   42.9
51      2007    150.7   41.7

Use both predictors. From the previous two exercises, we conclude that year and soybean may be useful together in a model for predicting corn yield. Run this multiple regression.

a)       Explain the results of the ANOVA F test. Give the null and alternate hypothesis, test statistic with degrees of freedom, and p-value. What do you conclude?

b)      What percent of the variation in corn yield in explained by these two variables? Compare it with the percent explained in the previous simple linear regression models.

c)       State the regression model. Why do the coefficients for year and soybean differ from those in the previous exercises?

d)      Summarize the significance test results for the regression coefficients for year and soybean yield.

e)      Give a 95% confidence interval for each of these coefficients.

f)        Plot the residual versus year and soybean yield. What do you conclude?