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18) Add trendline, regression

Saeko has a yarn shop and wants to test her theory on what types of colors she is selling.She believes that Black, White, the Primary Colors, and Tertiary colors sell in equal amounts.Test Saeko’s theory using the 5 step hypothesis testing analysis and Chi Square at the .10 level of significance.

(optional) Use the “Pivot Table Data” tab to create a pivot table that shows Saeko the number of yards that were sold in the various yarn types during the busiest weekend of her shop last year.

The pivot table should contain Color Type, Sum of Yards and Count of Color Type as Column Titles.

Here is the pivot table that you should have created. It is optional so that you can practice your pivot table skills.

Color Type Sum of Yards Count of Color Type

Black 19,762.00 23

Blue 8,127.00 20

Brown 8,027.00 13

Green 6,533.00 12

Purple 7,243.00 12

Red 5,194.00 10

White 17,649.00 26

Yellow 7,229.00 14

Grand Total 79,764.00 130

1) Using the pivot table that you just created, fill in the blanks in the following table:

Primary Colors consists of the sum of Blue, Red, and Yellow yarn sold

Tertiary Colors consists of the sum of Brown, Green, and Purple Colors Sold.

The Total in this chart must equal the Grand Total, Cell D16 in the above table.

Color Type Sum of Yards

Black

White

Primary Colors

Tertiary Colors

Total

This table represents the observed data in the Chi Square analysis.

Find the Expected values for each of the colors. Saeko expects that the colors sell in equal amounts.

Color Type Sum of Yards

Black

White

Primary Colors

Tertiary Colors

Total

Subtract the Expected values from the observed values

Color Type Sum of Yards

Black

White

Primary Colors

Tertiary Colors

Square the values just found

Color Type Sum of Yards

Black

White

Primary Colors

Tertiary Colors

Divide each square by the expected value and add together

Color Type Sum of Yards

Black

White

Primary Colors

Tertiary Colors

Total

This total is your Chi Square test statistic

2) Use the 5 step hypothesis testing procedure to determine if Saeko’s hypothesis that the colors sell in equal amounts is true.

What is the null hypothesis?

What is the alternative hypothesis?

What is the level of significance?

What is the Chi Square test statistic? –

3) What is the Chi Square critical Value? Use =CHISQ.INV()

4) What is your answer to Saeko?

Customer

Color Name

Color Type

Yards

Meters

1

Coriander

White

1,067.00

975.66

2

Black

Black

917.00

838.50

3

Daffodil

Yellow

762.00

696.77

4

Black

Black

735.00

672.08

5

Opal

Blue

551.00

503.83

6

Toffee

Brown

709.00

648.31

7

Ruby

Red

792.00

724.20

8

Ash

Blue

830.00

758.95

9

Black

Black

670.00

612.65

10

Ash

Blue

292.00

267.00

11

Black

Black

744.00

680.31

12

Whirlpool

Blue

943.00

862.28

13

Verde

Green

947.00

865.94

14

Regal

Purple

945.00

864.11

15

Lynx

Brown

774.00

707.75

16

Yellow Rose

Yellow

801.00

732.43

17

Chocolate

Brown

750.00

685.80

18

Mist

White

629.00

575.16

19

Whirlpool

Blue

113.00

103.33

20

Alfalfa

Green

344.00

314.55

21

Ruby

Red

162.00

148.13

22

Verde

Green

964.00

881.48

23

Sky

White

517.00

472.74

24

Black

Black

1,223.00

1,118.31

25

Whirlpool

Blue

200.00

182.88

26

Black

Black

879.00

803.76

27

Mist

White

999.00

913.49

28

Alfalfa

Green

598.00

546.81

29

Jade

Green

662.00

605.33

30

Yellow Rose

Yellow

368.00

336.50

31

Cream

White

529.00

483.72

32

Black

Black

1,100.00

1,005.84

33

Ruby

Red

870.00

795.53

34

Mist

White

342.00

312.72

35

Yellow Rose

Yellow

747.00

683.06

36

Black

Black

1,160.00

1,060.70

37

Sky

White

628.00

574.24

38

Periwinkle

Purple

185.00

169.16

39

Coriander

White

978.00

894.28

40

Black

Black

607.00

555.04

41

Yellow Rose

Yellow

387.00

353.87

42

Black

Black

255.00

233.17

43

Periwinkle

Purple

742.00

678.48

44

Black

Black

414.00

378.56

45

Blush

Red

345.00

315.47

46

Black

Black

892.00

815.64

47

Mist

White

727.00

664.77

48

Coriander

White

584.00

534.01

49

Cream

White

321.00

293.52

50

Verde

Green

478.00

437.08

51

Black

Black

931.00

851.31

52

Daffodil

Yellow

539.00

492.86

53

Chocolate

Brown

767.00

701.34

54

Daffodil

Yellow

369.00

337.41

55

Regal

Purple

378.00

345.64

56

Daffodil

Yellow

376.00

343.81

57

Coriander

White

957.00

875.08

58

Black

Black

929.00

849.48

59

Black

Black

959.00

876.91

60

Lynx

Brown

994.00

908.91

61

Periwinkle

Purple

714.00

652.88

62

Daffodil

Yellow

912.00

833.93

63

Coriander

White

776.00

709.57

64

Verde

Green

895.00

818.39

65

Lynx

Brown

706.00

645.57

66

Alfalfa

Green

105.00

96.01

67

Cream

White

165.00

150.88

68

Daffodil

Yellow

505.00

461.77

69

Periwinkle

Purple

661.00

604.42

70

Cream

White

226.00

206.65

71

Black

Black

472.00

431.60

72

Opal

Blue

184.00

168.25

73

Cream

White

191.00

174.65

74

Cream

White

238.00

217.63

75

Coriander

White

894.00

817.47

76

Mist

White

488.00

446.23

77

Verde

Green

400.00

365.76

78

Black

Black

1,618.00

1,479.50

79

Blush

Red

374.00

341.99

80

Opal

Blue

359.00

328.27

81

Daffodil

Yellow

553.00

505.66

82

Mist

White

439.00

401.42

83

Alfalfa

Green

448.00

409.65

84

Jade

Green

290.00

265.18

85

Ruby

Red

907.00

829.36

86

Verde

Green

402.00

367.59

87

Cream

White

123.00

112.47

88

Black

Black

981.00

897.03

89

Chocolate

Brown

247.00

225.86

90

Regal

Purple

805.00

736.09

91

Sky

White

358.00

327.36

92

Regal

Purple

461.00

421.54

93

Yellow Rose

Yellow

540.00

493.78

94

Lynx

Brown

964.00

881.48

95

Regal

Purple

317.00

289.86

96

Ash

Blue

190.00

173.74

97

Periwinkle

Purple

423.00

386.79

98

Black

Black

1,761.00

1,610.26

99

Black

Black

912.00

833.93

100

Blush

Red

258.00

235.92

101

Regal

Purple

968.00

885.14

102

Sapphire

Blue

517.00

472.74

103

Whirlpool

Blue

362.00

331.01

104

Yellow Rose

Yellow

125.00

114.30

105

Whirlpool

Blue

504.00

460.86

106

Sapphire

Blue

427.00

390.45

107

Chocolate

Brown

557.00

509.32

108

Toffee

Brown

498.00

455.37

109

Sapphire

Blue

216.00

197.51

110

Whirlpool

Blue

174.00

159.11

111

Black

Black

470.00

429.77

112

Regal

Purple

644.00

588.87

113

Opal

Blue

436.00

398.68

114

Blush

Red

768.00

702.26

115

Coriander

White

1,456.00

1,331.37

116

Whirlpool

Blue

385.00

352.04

117

Ash

Blue

869.00

794.61

118

Blush

Red

416.00

380.39

119

Black

Black

634.00

579.73

120

Ruby

Red

302.00

276.15

121

Mist

White

892.00

815.64

122

Chocolate

Brown

240.00

219.46

123

Opal

Blue

523.00

478.23

124

Toffee

Brown

710.00

649.22

125

Yellow Rose

Yellow

245.00

224.03

126

Sky

White

736.00

673.00

127

White

White

2,389.00

2,184.50

128

Black

Black

499.00

456.29

129

Chocolate

Brown

111.00

101.50

130

Ash

Blue

52.00

47.55

Saeko owns a yarn shop and want to expands her color selection.

Before she expands her colors, she wants to find out if her customers prefer one brand over another brand. Specifically, she is interested in three different types of bison yarn.

As an experiment, she randomly selected 21 different days and recorded the sales of each brand. At the .01 significance level, can she conclude that there is a difference in preference between the brands?

Misa’s Bison Yak-et-ty-Yaks Buffalo Yarns

343 365 360

308 368 346

349 351 381

304 339 306

348 366 314

346 331 307

Total 1,998.00 2,120.00 2,014.00

5) What is the null hypothesis?

What is the alternative hypothesis?

What is the level of significance?

6) Use Tools – Data Analysis – ANOVA:Single Factor

to find the F statistic:

7) From the ANOVA ooutput: What is the F value?

8) What is the F critical value?

9) What is your decision?

Studies have shown that the frequency with which shoppers browse Internet retailers is related to the frequency with which they actually purchase products and/or services online. The following data show respondents age and answer to the question “How many minutes do you browse online retailers per week?”

Age (X) Time (Y)

13 5662

19 4549

16 3772

44 1872

32 2799

52 1355

39 1966

15 5682

40 1602

53 1186

48 1832

37 2253

36 2241

42 1001

30 2474

42 1943

28 3021

11 5682

32 2192

39 1784

23 2707

37 1801

17 4827

11 2693

18 4340

50 1399

52 1593

9 9154

41 1504

26 2627

30 2575

32 2711

53 2368

10) Use Data > Data Analysis > Correlation to compute the correlation checking the Labels checkbox.

11) Use the Excel function =CORREL to compute the correlation. If answers for #1 and 2 do not agree, there is an error.

The strength of the correlation motivates further examination.

12) a) Insert Scatter (X, Y) plot linked to the data on this sheet with Age on the horizontal (X) axis.

b) Add to your chart: the chart name, vertical axis label, and horizontal axis label. c) Complete the chart by adding Trendline and checking boxes

Read directly from the chart:

13) a) Intercept =

b) Slope =

c) R2 =

Perform Data > Data Analysis > Regression.

14) Highlight the Y-intercept with yellow. Highlight the X variable in blue. Highlight the total standard error in orange

Use Excel to predict the number of minutes spent by a 37-year old shopper. Enter = followed by the regression formula.

15) Enter the intercept and slope into the formula by clicking on the cells in the regression output with the results.

16) Is it appropriate to use this data to predict the amount of time that a 68-year-old will be on the Internet?

If yes, what is the amount of time, if no, why?

17) On this worksheet, make an XY scatter plot linked to the following data:

X Y

92 22

87 23

102 23

80 25

91 27

100 20

95 21

109 19

77 28

100 221

98 25

89 27

97 23

93 22

89 27

91 22

97 21

105 21

88 22

83 24

86 27

89 26

79 30

88 22

94 24

18) Add trendline, regression equation and r squared to the plot. Add this title. (“Scatterplot of X and Y Data”)

19) The scatterplot reveals a point outside the point pattern. Copy the data to a new location in the worksheet. You now have 2 sets of data.

Data that are more tha 1.5 IQR below Q1 or more than 1.5 IQR above Q3 are considered outliers and must be investigated.

It was determined that the outlying point resulted from data entry error. Remove the outlier in the copy of the data.

Make a new scatterplot linked to the cleaned data without the outlier, and add title (“Scatterplot without Outlier,”) trendline, and regression equation label.

20) Compare the regression equations of the two plots. How did removal of the outlier affect the slope and R2?

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