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# Stats problems

Question # 00011786
Subject: Statistics
Due on: 04/29/2014
Posted On: 04/08/2014 04:50 PM

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1. Divide your data in half, your first 8 observations and your last 7 observations. Then use ANOVA to test to see if there is a significant difference between the two halves of your data. This list of Webpages that Perform Statistical Calculations has several ANOVA calculators.

2. Take your data and arrange it in the order you collected it. Count the total number of observations you have, and label this number N. Then create another set of data starting from one and increasing by one until you reach N. For example, if you have 10 observations, then your new set of data would be (1, 2, 3, 4, 5, 6, 7, 8, 9, 10). This set of data is called a time series. Run a regression using your original set of data as your dependent variable, and your time series as an independent variable. Use the simple regression calculation page to calculate your regression. Write a paper reporting your results and any conclusions that can be reached with it.

Data I collected: The session long project assignment for Module 4 is to continue collecting data related to your life. The original assignment was to collect 10 days of data on a particular variable and apply probability. Module 4 SLPâ€™s requires an additional 5 more days of data. I selected data consisting of the number of calls I receive on my 8 hour shift for the past 10 Days. Listed is the data that was collected for a 10 day period to include the 5 additional days for this assignment.

Day Calls Received Hrs Worked
1 Monday 27 8
2 Tuesday 34 8
3 Wednesday 13 8
4 Thursday 15 8
5 Friday 28 8
6Monday 33 8
7Tuesday 26 8
8Wednesday 18 8
9 Thursday 16 8
10 Friday 30 8

27, 34, 13, 15, 28, 33, 26, 18, 16 and 30. Placed in numerical order the numbers are as follows:
13, 15, 16, 18, 26, 27, 28, 30, 33, and 34
Listed below is data for 5 additional days:
Day Calls Received Hrs Worked
1 Monday 38 8
2 Tuesday 31 8
3 Wednesday 25 8
4 Thursday 30 8
5 Friday 29 8

Placed in numerical order the numbers are as follows:
13, 15, 16, 18, 25, 26, 27, 28, 29, 30, 30, 31, 33, 34, 38, add all 15 entries 393
Now that I have my total I need to divide it by the number of days 15 393/15 = 26 (mean)

To find the median you simply select the middle number in a set and divide by two. In my case
I have 28 and 29, so I would add the numbers 28+29 =57
Then divide the answer by (2) 57/2= 28.5 or 29 rounded up. (median)

The mode is simply the number that appears the most, from my group of numbers the number15
occurred the most. So for my example 30 is the mode.

Is the larger sample changing anything? Yes, my numbers have increased for the Mean, Median and Mode.
Is your mean increasing or decreasing? Increased
Do you think the current sample you have is enough to paint an accurate picture, or do you need a much larger sample? I feel the information I have would not paint an accurate picture. I would need at least 30 days worth of data, and factor in the holiday season call flow.

1) Divide your data in half, your first 8 observations and your last 7 observations. Then use ANOVA to test to see if there is a significant difference between the two halves of your data. This list of Webpages that Perform Statistical Calculations has several ANOVA calculators.
2) Take your data and arrange it in the order you collected it. Count the total number of observations you have, and label this number N. Then create another set of data starting from one and increasing by one until you reach N. For example, if you have 10 observations, then your new set of data would be (1, 2, 3, 4, 5, 6, 7, 8, 9, 10). This set of data is called a time series. Run a regression using your original set of data as your dependent variable, and your time series as an independent variable. Use the simple regression calculation page to calculate your regression. Write a paper reporting your results and any conclusions that can be reached with it.

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#### Stats problems

Tutorial # 00011360
Posted On: 04/08/2014 04:51 PM
Posted By:
msmonopoly
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Preview: the xxxxxxxxxx model xxxxxxx for the xxxx series analysis xx the xxxxx xxxxxxxx We xxx see that xxxxxxxxxx coefficient (?) xx 0 xxx xxx intercept xxx is 22 xxx with a xxxxxxxx error xx x 446 xxx 4 055 xxxxxxxxxxxx Further the x value xx xxxxx to xx 0 324 xxxxx the p xxxxx > x xx it xxx be concluded xxxx the regression xxxxxxxxxxx (?) xx xxx significant xx 5% level xx significance Table xxxx indicates xxx xxxxx of xxxxxxxxxxx coefficient to xx 0 273 xxx.....
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