California National University Data Analytics Excel Task

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User Generated

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vojlyvrpblbgr

Subject

Business Finance

School

California National University

Description

Format: Answer these questions using an Excel workbook and include a problem per sheet. Name the sheets with the corresponding problem number in the textbook, for instance 1 0 - 1 4 or 1 0 - 1 8 . All problems have already a guide to make the network graphs and calculations. Follow the format in the excel document provided in Course Resources for HW4 .

Chapter 3 (New) Statistics

Chapter 9(or Ch-15 ) Time Searies and Forcasting

Chapter 10(New ) Staitistical Method for Quality Control

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Variable 91 78 93 57 75 52 99 80 97 62 71 69 72 89 66 75 79 75 72 76 104 74 62 68 97 105 77 65 80 109 85 97 88 68 83 68 71 69 Sample Descriptive Statistics Sample Size = 50 Mean = 78.98 Standard Deviation = 13.99 Coefficient of Variation = 17.72% Variance = 195.78 Standard Error of Mean (m)= 1.98 95% CI Upper Limit for m = 106.40 95% CI Lower Limit for m = 51.56 Median = 75.50 Mode = 62.00 Skewness = 0.48 Kurtosis = -0.60 Minimum = 52.00 Maximum = 109.00 Range = 57.00 Sum of data = 3949 Sum of Squares of data = 321485 67 74 62 82 98 101 79 105 79 69 62 73 x Mean Std Dev z-score Prob (> x) Prob (< x) Sample Observation 1 Observation 2 Observation 3 Observation 4 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Grand Averages: m= s= UCL = LCL = Rbar = UCL = LCL = #DIV/0! #DIV/0! #DIV/0! #DIV/0! 0.0000 0 0.0000 Grand Std Dev: Observation 5 xbar R 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 Averages: #### 0.0000 Std Dev: #### Xbar Plotting Values #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! Rbar Plotting Va 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Rbar Plotting Values 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.9000 0.8000 0.7000 Axis Title 0.6000 0.5000 0.4000 0.3000 0.2000 0.1000 0.0000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Batch MEANS Process Mean LCL UCL 16 17 18 19 20 1.0000 0.9000 0.8000 0.7000 0.6000 0.5000 0.4000 0.3000 0.2000 0.1000 0.0000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 UCL LCL Process Mean Batch Means 16 17 18 19 20 INPUTS Number of Periods of Data Collected = PROCESS Value Time Series 1.2 1 0.8 Value Period 0.6 0.4 0.2 0 0 5 10 15 Time Period Sample Descriptive Statistics Sample Size = Mean = Standard Deviation = Variance = Standard Error of Mean (m)= 95% CI Lower Limit for m = 95% CI Upper Limit for m = Median = Mode = Skewness = Kurtosis = Maximum = Minimum = Range = Coefficient of Variation = 20 25 30 INPUTS OUTPUTS Number of Periods in Moving Average = Forecast = Number of Periods of Data Collected = MSE = MAD = PROCESS Period Value Forecast Error Absolute Error Absolute Error Squared % Error MAPE = LAD = INPUTS OUTPUTS Number of Periods in Moving Average Number of Periods of Data Collected Past Period 1 2 = Forecast = = 3 MSE = MAD = 4 5 6 Absolute Error Absolute Error Squared % Error Weighting PROCESS Period Value Forecast Error MAPE = LAD 7 = 8 9 10 11 12 13 14 15 INPUTS OUTPUTS Number of Periods of Data Collected = Forecast = Smoothing Constant (alpha) = MSE = Initial Forecast Value = MAD = PROCESS Period Value Forecast Error Absolute Error Absolute Error Squared % Error MAPE = LAD = INPUTS OUTPUTS Number of Periods of Data Collected = t value = Period = MSE = MAD = OUTPUTS Period Forecast PROCESS Period Value Forecast Residual Absolute Residual Absolute Error Error Squared % Error Forecast = R sqrd = Std Err = MAPE = Intercpt = LAD = Slope = INPUTS OUTPUTS Number of Periods of Data Collected = Smoothing Constant (alpha) = Period Smoothing Constant (gamma) = MSE = Initial Forecast Value (Level) = MAD = Initial Forecast Value (Trend) = = OUTPUTS Period Forecast PROCESS Period Value Forecast Forecast Level Trend Absolute Forecast Error Error Forecast = MAPE = LAD = Error Absolute Squared % Error INPUTS OUTPUTS Number of Periods of Data Collected = Number of Seasonal Periods in Year = Period = MSE = MAD = OUTPUTS Period Forecast PROCESS Period Centered Value Moving Av. Seasonal/ Deseasoned Random Values Forecast Error Forecast MAPE = Intercpt = LAD = Slope = Absolute Error Absolute Error Squared % Error INPUTS Number of Periods of Data Collected = Number of Seasons = REGRESSION INPUTS Value Seasonal Factors Period 1 2 3 4 5 6 7 8 9 10 11 MNS407 – Week 4 Assignment Problems Last, First Name: ___________ • • Textbook, Statistics for Business and Economics, 13 e: o Chapter 3, Descriptive Statistics o Chapter 10, Statistical Methods for Quality Control Textbook, Management Science, 14e: o Chapter 15, Time Series Analysis and Forecasting Chapter 3, Problem 62 (Page 147) Chapter 3, Problem 65(page-148) Chapter 3, Problem 67(Page-148-149) 1 Chapter 10, Problem 20(Page-541) 2 Chapter -9 (or 15), Problem 5 (page -769) Chapter-9(or Ch- 15), Problem 11(page 770) 3 Chapter-9)(or Ch- 15), Problem 21(page 772) 4 Chapter-9 (or Ch-15) , Problem 22(page (773) 5
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Explanation & Answer:

3 spreadsheets

Tags: descriptive statistics variance skewness Standard Deviation Standard Error of Mean

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Explanation & Answer

Completed the assignment

Variable
6
1
5
3
7
3
0
3
1
3
4
1
2
4
1
0
5
6
3
1

Sample Descriptive Statistics
Sample Size =
20
Mean =
2.95
Standard Deviation =
2.09
Coefficient of Variation =
70.83%
Variance =
4.37
Standard Error of Mean (m)=
0.47
95% CI Upper Limit for m =
7.05
95% CI Lower Limit for m =
-1.15
Median =
3.00
Mode =
1.00
Skewness =
0.34
Kurtosis =
-0.87
Minimum =
0.00
Maximum =
7.00
Range =
7.00
Sum of data =
59
Sum of Squares of data =
257
First Quartile =
1
Third Quiartile =
4.25
Lower Limit =
-4.625
Upper Limit =
10.375

The distribution is therefore

The distribution is therefore positively skewed meaning the the shape is expected to be skewed to the right.

Variable
6
5
10
5
6
9
9
5
9
5
8
7
8
6
9
8
9
6
10
8

Sample Descriptive Statistics
Sample Size =
20
Mean =
7.40
Standard Deviation =
1.76
Coefficient of Variation =
23.77%
Variance =
3.09
Standard Error of Mean (m)=
0.39
95% CI Upper Limit for m =
10.85
95% CI Lower Limit for m =
3.95
Median =
8.00
Mode =
9.00
Skewness =
-0.11
Kurtosis =
-1.48
Minimum =
5.00
Maximum =
10.00
Range =
5.00
Sum of data =
148
Sum of Squares of data =
1154

Public Transportation

Automobile
28

29

29
32
37

31
33
32

33

34

25

30

29
32

31
32

41

35

34

33

I prefer the automobile

Sample Descriptive Statistics
Sample Size =
Mean =
Standard Deviation =
Coefficient of Variation =
Variance =
Standard Error of Mean (m)=
95% CI Upper Limit for m =
95% CI Lower Limit for m =
Median =
Mode =
Skewness =
Kurtosis =
Minimum =
Maximum =
Range =
Sum of data =
Sum of Squares of data =

criptive Statistics
10
32.00
4.64
14.51%
21.56
1.47
41.10
22.90
32.00
29.00
0.56
0.37
25.00
41.00
16.00
320
10434

10
32
1.83
0.06
3.33
0.58
35.58
28.42
32
31
-0.45
29
35
6
320
10434

The box plotsho lower valiability with automobile transportati

omobile transportation and thus supports the conclusion in part c

Sample Observation 1 Observation 2 Observation 3 Observation 4
1
3.0500
3.0800
3.0700
3.1100
2
3.1300
3.0700
3.0500
3.1000
3
3.0600
3.0400
3.1200
3.1100
4
3.0900
3.0800
3.0900
3.0900
5
3.1000
3.0600
3.0600
3.0700
6
3.0800
3.1000
3.1300
3.0300
7
3.0600
3.0600
3.0800
3.1000
8
3.1100
3.0800
3.0700
3.0700
9
3.9000
3.0900
3.0800
3.0700
10
3.0600
3.1100
3.0700
3.0900
11
12
13
14
15
16
17
18
19
20
Grand Averages:
m=
s=
UCL =
LCL =

3.0818
0.1178
3.1124
3.0512

Rbar =
UCL =
LCL =

0.0530
0.1120
0.0000

Grand Std Dev:

Observation 5
3.1100
3.1000
3.1000
3.0700
3.0800
3.0600
3.0800
3.0700
3.0900
3.0700

xbar
3.0840
3.0900
3.0860
3.0840
3.0740
3.0800
3.0760
3.0800
3.0840
3.0800

R
0.0600
0.0800
0.0800
0.0200
0.0400
0.1000
0.0400
0.0400
0.0200
0.0500

Averages:

3.0818 0.0530

Std Dev:

0.1178

Xbar Plotting Values
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398
2.9238
3.0818
3.2398

Rbar Plotting Va
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204
0.11204

Rbar Plotting Values
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000
0.0530
0.0000

LCL

1

3.0840

3.0818

3.1124 3.0512

2

3.0900

3.0818

3.1124 3.0512

3

3.0860

3.0818

3.1124 3.0512

4

3.0840

3.0818

3.1124 3.0512

5

3.0740

3.0818

3.1124 3.0512

6

3.0800

3.0818

3.1124 3.0512

7

3.0760

3.0818

3.1124 3.0512

8

3.0800

3.0818

3.1124 3.0512

9

3.0840

3.0818

3.1124 3.0512

10

3.0800

3.0818

3.1124 3.0512

3.1200
3.1100
3.1000

Sample Mean

Sample Batch Means Process Mean UCL

3.0900
3.0800
3.0700
3.0600
3.0500
3.0400

0

2

4

All sample means are within the control limits, this confirms that th

Xbar Chart

Batch Means
Process Mean

UCL
LCL

6

8

10

12

Sample

mits, this confirms that the process as controled during the sampling period.

UCL
#####
#####
#####
#####
#####
#####
#####
#####
#####
#####

LCL
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
...