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MALL TRENDS By: Cameron Lance, Denny Burns, and Dominic Raguz

MALL TRENDS

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MALL TRENDS. By: Cameron Lance, Denny Burns, and Dominic Raguz. TOPIC. We will observe people going into three different stores Pac sun Hollister GameStop We will go to two different malls at two different times Montgomery Mall Willow Grove Mall. What We Wanted To Research. - PowerPoint PPT Presentation

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Page 1: MALL TRENDS

MALL TRENDSBy: Cameron Lance, Denny Burns, and Dominic Raguz

Page 2: MALL TRENDS

• We will observe people going into three different stores– Pac sun– Hollister– GameStop

• We will go to two different malls at two different times– Montgomery Mall– Willow Grove Mall

TOPIC

Page 3: MALL TRENDS

• We wanted to see if certain stores appealed to specific genders

• Testing to see if stereotypes were true about certain stores– Hollister would have more females– GameStop would have more males– Pac Sun would be a neutral store

What We Wanted To Research

Page 4: MALL TRENDS

• We wanted to see if males or females are more likely to purchase goods in a store-We want to find out the overall trend between genders as to who buys more when they enter a store

• We think that females are more likely to buy something as opposed to males

What We Wanted To Research

Page 5: MALL TRENDS

• We wanted to see which store is the most popular out of the three observed– See which store has more people going in and out

of it

• Between the three, we think that Pac Sun will have the most people because they are advertised as a neutral store, appealing to males and females

What We Wanted To Research

Page 6: MALL TRENDS

• We are conducting an observational study to collect our data– We will sit at a distance from each store for ninety

minutes– One person at each store for a ninety minute

interval, making observations of gender, whether they purchase something, and how many people visit the store

– We are counting everybody that walks in except for babies and anybody that doesn’t have a choice

Procedure

Page 7: MALL TRENDS

• After the ninety minute observational period, we went to the other mall

• We changed the store we observed to make sure the results were consistent

• Next day did the same thing at each mall, but at different times

Procedure

Page 8: MALL TRENDS

MONTGOMERY MALL - GAMESTOP

Buy

No Buy

0 5 10 15 20 25 30 35 40 45

FemalesMales

Number of Buyers

28

39

9

12

Page 9: MALL TRENDS

WILLOW GROVE MALL-GAMESTOP

Buy

No-Buy

0 10 20 30 40 50 60

FemalesMales

Number Of Buyers

3312

5127

Page 10: MALL TRENDS

Males (Buy)

Males (Didn't Buy)

Females (Buy)

Females (Didn’t Buy)

0 10 20 30 40 50 60 70 80 90 100

CONCLUSION - GameStop

Page 11: MALL TRENDS

MONTGOMERY MALL - HOLLISTER

Buy

No Buy

0 10 20 30 40 50 60 70

FemalesMales

Number of Buyers

59

28

35

16

Page 12: MALL TRENDS

WILLOW GROVE MALL-HOLLISTER

Buy

No-Buy

0 20 40 60 80 100 120

FemalesMales

Number Of Buyers

114

39

1738

Page 13: MALL TRENDS

CONCLUSION - HOLLISTER

Males (Buy)

Males (Didn't Buy)

Females (Buy)

Females (Didn’t Buy)

0 20 40 60 80 100 120 140 160 180 200

Page 14: MALL TRENDS

MONTGOMERY MALL - PACSUN

Buy

No Buy

0 5 10 15 20 25 30 35 40 45

FemalesMales

Number of Buyers

37

41

32

25

Page 15: MALL TRENDS

WILLOW GROVE MALL-PACSUN

Buy

No-Buy

0 10 20 30 40 50 60 70 80 90 100

FemalesMales

Number of Buyers

87

2324

84

Page 16: MALL TRENDS

Males (Buy)

Males (Didn't Buy)

Females (Buy)

Females (Didn’t Buy)

0 20 40 60 80 100 120 140

CONCLUSION – Pac Sun

Page 17: MALL TRENDS

Chi-Square Test of Association – Pac Sun

ASSUMPTIONS

1. 2 SRS

2. All expected counts > 5

CHECKS

1. Was not an SRS, we counted everyone; but we did the test anyways

2. HYPOTHESES

HO: There is NO association between the gender of someone who buys a product at Pac Sun (independent of one another)

HA: There IS AN association between the gender of someone who buys a product at Pac Sun

Page 18: MALL TRENDS

∑Chi-Square Test of AssociationX2 = (observed – expected)2

expected

X2 = (48 – 53.587)2

53.87 X2 = 1.647

P(X2 > 1.647 df = 1) = .1993

CONCLUSIONWe fail to reject Ho because a p-value of .1993 > α = .05. We have sufficient evidence that there is no association between the gender of someone who buys a product at Pac Sun.

∑ + (128-122.41) 2

122.41

Page 19: MALL TRENDS

Chi-Square Test of Association – Hollister

ASSUMPTIONS

1. 2 SRS

2. All expected counts > 5

CHECKS

1. Was not an SRS, we counted everyone; but we did the test anyways

2. HYPOTHESES

HO: There is NO association between the gender of someone who buys a product at Hollister (independent of one another)

HA: There IS AN association between the gender of someone who buys a product at Hollister

Page 20: MALL TRENDS

∑Chi-Square Test of AssociationX2 = (observed – expected)2

expected

X2 = (33 – 30.233)2

30.233 X2 = 1.647

P(X2 > .511 df = 1) = .474

CONCLUSIONWe fail to reject Ho because a p-value of .474 > α = .05. We have sufficient evidence that there is no association between which gender buys something at Hollister.

∑ + (67-69.767) 2

69.767

Page 21: MALL TRENDS

Chi-Square Test of Association – GameStop

ASSUMPTIONS

1. 2 SRS

2. All expected counts > 5

CHECKS

1. Was not an SRS, we counted everyone; but we did the test anyways

2. HYPOTHESES

HO: There is NO an association between the gender of someone buying an item at GameStop (independent of one another)

HA: There IS AN association between the gender of someone buying an item at GameStop

Page 22: MALL TRENDS

∑Chi-Square Test of AssociationX2 = (observed – expected)2

expected

X2 = (35 –34.826)2

34.826 X2 = .003

P(X2 > .003 df = 1) = .954

CONCLUSIONWe fail to reject Ho because a p-value of .954 > α = .05. We have sufficient evidence that there is no association between the gender of a person who buys something at GameStop.

∑ + (90-90.174) 2

90.174

Page 23: MALL TRENDS

• Assumptions Checks1. SRS 1.assumed2. Normal population 2.n ≥ 30 Or N≥303. Population ≥ 10n 3. 10n ≤

Population

One Proportion Z-Test-Pac Sun

Page 24: MALL TRENDS

One Proportion Z-Test-Pac Sun

Ho: p=0.5Ha: p≠0.5

Z= = -0.317 npppp)1(

ˆ

2*P(z<-0.317)= .751We fail to reject Ho because p-value of 0.751 > α=0.05

We have sufficient evidence that the true percent of males is equal to 50%

Page 25: MALL TRENDS

• Assumptions Checks1. SRS 1.assumed2. Normal population 2.n ≥ 30 Or N≥303. Population ≥ 10n 3. 10n ≤

Population

One Proportion Z-Test-Hollister

Page 26: MALL TRENDS

One Proportion Z-Test-Hollister

Ho: p=0.5Ha: p<0.5

Z= =-7.764npppp)1(

ˆ

P(z<-7.764)=8.3*10^-15We reject Ho because p-value of 8.3*10^-15 < α=0.5We have sufficient evidence that the true percent of males who go to Hollister is less than 50%

Page 27: MALL TRENDS

• Assumptions Checks1. SRS 1.assumed2. Normal population 2.n ≥ 30 Or N≥303. Population ≥ 10n 3. 10n ≤

Population

One Proportion Z-Test-GameStop

Page 28: MALL TRENDS

One Proportion Z-Test-GameStop

Ho: p=0.5Ha: p>0.5

Z= =3.456 npppp)1(

ˆ

P(z>3.456)=.0003We reject Ho because p-value of .0003 > α=0.5We have sufficient evidence that the true percent of males who go to GameStop is greater than 50%

Page 29: MALL TRENDS

• GameStop– We found that at the mall more males go into

GameStop than females– However, if a females goes in, she is more likely to buy

something • Hollister – We found that at the mall more females go into

Hollister than males– However, if a male goes in, he is more likely to buy

something

Overall Conclusions

Page 30: MALL TRENDS

• Pac Sun– We found that at the mall Pac Sun is a neutral

store with about the same number of males and females going in

Overall Conclusions

Page 31: MALL TRENDS

• Stores having a sale could lead to more people walking in or buying things

• We only went to two different malls at times that suited us

• If we missed people walking in or if someone went in twice during the time we observed

• We could of missed someone if they were in a group of people that walked out and we miscounted

Bias and Error

Page 32: MALL TRENDS

• Our conclusions were what we thought would happen– GameStop is male dominated– Hollister is female dominated– Pac Sun is neutral

• We loved doing stat outside of school!!!!!• It was a lot of waiting around and taking data but we

found ways to entertain ourselves • It was rewarding to get all our results after our hard

work

Personal Opinions and Conclusions