California State University San Marcos Smoking & GPA Analysispublic.csusm.edu/fangfang/Teaching/BUS304/Team... · 2008-05-19 · The following data was compiled over a multiple week

CSUSM 1

California State University San Marcos

Smoking & GPA Analysis

Business Statistics 304

Spring 2008 Semester

Professor Fang Fang

Written by:

Walter Evans

Farzana Mohsini

Sheryl Lejano

Ryan Thomas

CSUSM 2

Introduction

Our team set out with the intention of researching, organizing and statistically analyzing

the smoking population here at California State University San Marcos. We sought out to prove

or disprove a negative, positive or neutral correlation between a student’s smoking habits on

campus and the effect on the student’s level of success in regards to their Grade Point Average.

By proving or disproving a cause and effect relationship between student smoking and student

success, the result would be a course of action in either accommodating the smoking population

at CSUSM or making efforts to inform, council and promote a lesser degree of smoking on

campus. By doing this survey, it will help us plan and implement smoking intervention programs

for California State University San Marcos. These programs may be helpful in preventing and/or

correcting the habit of tobacco use in school. Our team understands smoking is a habit and a

social norm that has been practiced through out history. We sought it necessary to examine such

an issue given the seriousness of the diseases that will result from the habit as well as the existing

high prevelant nature of smokers on campus. The campus acts as a sample size in itself for the

community of San Marcos and really San Diego County.

Our team is aware of the numerous variables in existence that may negatively or

positively contribute to our research outcome; however the standard in which we will collect

data, develop an outline for calculations and analyze the results will be as accurate as possible

for this level of research we are performing. To properly evaluate the extensiveness of a student

smoker’s habit and the level of success a student has accomplished, our research will identify the

following points as outlined in our survey:

CSUSM 3

Cal State San Marcos Smoking Survey

Gender: Male Female

Class: Freshman Sophomore Junior Senior

Age: 17-20 21-24 25-28 29-32 33-36 37-40 >40

What is your major? _____________

What is your G.P.A.? <= 2.0 2.01~2.4 2.41~2.80 2.81~3.20 3.21~3.60 >3.6

Do you have a family history of smoking? YES NO

When I see a person smoking, it…

makes him/her more attractive.

makes him/her less attractive

has no impact on their attractiveness.

Would you date a person who is smoker? YES NO

Do you smoke tobacco?

YES NO

If YES, how many times do you smoke a day?

1-3 times 4-6 times 7-9 times >10 times

How long have you been smoking? < 1 year 1-3 years 3-10 years >10 years

Thank you for your help on this research project! It is greatly appreciated!

CSUSM 4

Methodology

We proceeded in our research by surveying 105 students on campus to operate as a

population size and represent California State University San Marcos. We proceeded to

randomly distribute our surveys on campus within classroom settings. We intentionally

distributed the surveys amongst classroom students in both major distinct and general elective

classes. Our data has offered us information on the following components:

Smoking Habit

• Time of day (cigarettes/day)

• Duration of smoking

• Family History of smoking

• Student smoking percentage

• Number of student smokers

Success as a Student

• Major.

• GPA Range.

• Graduation timeframe.

• Number of Credit Units on average per semester.

• Number of work hours outside of class devoted to study.

As a team we understand the social-cultural dimension of acceptance related to smoking

in the general environment. Our team is evident of the fact, television campaigns, medical

studies, and legal testimony from tobacco corporations are concluding evidence of the negative

effects of smoking for long periods of time. Our team understands the external factors and

CSUSM 5

background information that is also relevant in the influencing of the smoking habit on and off

campus, those variables include:

• Health risks (first and second hand.)

• Cancer susceptibility.

• Based on time spent on campus in direct connection with smoking.

• Comparing and contrasting smoker comfort versus non-smoker discomfort.

• Non-smokers hidden annoyances toward smoking.

• Smoker’s awareness of nonsmokers.

• Determining possible reasons for smoking (stress, habit, social conformity?)

The following data was compiled over a multiple week time length during the day from

0900 to 1600, the optimal school hours. The data was organized utilizing an Excel Spreadsheet

for the purpose of sorting, formulating and graph/table generation. Our team performed regular

meetings inside class, outside class and on the weekends. Our teamwork was essential in

properly analyzing our research. We met on a number of occasions with our supervisor to

correctly understand and present the information prior to collecting the data and after.

CSUSM 6

Results

CSUSM 7

Data Collection and Organization

# Gender Class Age Major G.P.A. History Attractiveness Date? Smoke Per Day Years

1 m Senior 21-24 PSCI 2.41-2.80 no less yes no 0 0

2 m Senior 21-24 PSCI 2.81-3.20 no less no no 0 0

3 m Senior >40 PSCI 3.21-3.60 no less n/a no 0 0

4 f Junior 21-24 Social sci 3.21-3.60 yes less yes no 0 0

5 m sophomore 29-32 Criminology 2.01-2.40 no less no no 0 0

6 m sophomore 17-20 PSCI 2.81-3.20 yes none no no 0 0

7 f sophomore 17-20 Social sci 3.21-3.60 yes less no no 0 0

8 m sophomore 17-20 PSCI >3.6 no less no no 0 0

9 f Senior 25-28 Comm 2.41-2.80 no less no no 0 0

10 f Senior 25-28 PSCI 2.81-3.20 yes none yes no 0 0

11 f Senior 21-24 Comm 2.81-3.20 no less no no 0 0

12 m sophomore 17-20 PSCI 2.41-2.80 yes less no no 0 0

13 m Junior 21-24 Finance 2.81-3.20 yes less no no 0 0

14 f sophomore 17-20 PSCI 3.21-3.60 no less yes no 0 0

15 m Junior 17-20 PSCI 2.81-3.20 no less no no 0 0

16 f junior 21-24 PSCI 2.81-3.20 yes less yes no 0 0

17 m senior 21-24 PSCI 2.41-2.80 yes less no no 0 0

18 m junior 21-24 Business 2.81-3.20 no less no no 0 0

19 m junior 29-32 PSCI 3.21-3.60 no less no no 0 0

20 f senior 21-24 n/a 3.21-3.60 yes none yes no 0 0

21 m sophomore 17-20 PSCI 2.81-3.20 yes none yes yes 7 to 9 1 to 3

22 m senior 29-32 PSCI 2.41-2.80 yes none yes yes >10 3 to 10

23 m junior 25-28 History 3.21-3.60 no none yes yes 1 to 3 1 to 3

24 m junior 21-24 Finance 3.21-3.60 no less no no 0 0

25 m junior 21-24 Management 2.81-3.20 no less no no 0 0

26 f junior 17-20 Comm 2.81-3.20 no less no no 0 0

27 f junior 17-20 Human Devlp 3.21-3.60 yes less yes yes 1 to 3 < 1

28 m junior n/a Bussiness 2.41-2.80 no less no no 0 0

29 f junior 17-20 Bussiness 2.41-2.80 no less no no 0 0

30 f junior 17-20 Finance 3.21-3.60 no less no no 0 0

31 m junior 25-28 Mass Media 2.81-3.20 yes less no no 0 0

32 f junior 21-24 Literature >3.6 yes less no no 0 0

33 f junior 17-20 Management >3.6 no less no no 0 0

34 m junior 25-28 Mass Media 2.81-3.20 yes less no no 0 0

35 f junior 21-24 Nursing >3.6 yes less no no 0 0

36 m junior 25-28 Accounting 3.21-3.60 yes less no no 0 0

37 f junior 21-24 Human Devlp 2.81-3.20 yes less no no 0 0

CSUSM 8

38 f senior 21-24 Psychology 3.21-3.60 yes less no no 0 0

39 m junior 21-24 Marketing 2.81-3.20 yes none no no 0 0

40 m junior 21-24 Management 2.41-2.80 yes less no no 0 0

41 m junior 21-24 Management 2.41-2.80 yes none yes yes 1 to 3 <1


43 m junior 21-24 Accounting 2.81-3.20 no less no no 0 0

44 m junior 25-28 n/a >3.6 yes less no no 0 0

45 f senior 21-24 Management 2.01-2.40 no less no no 0 0

46 m senior 21-24 Management 2.41-2.80 n/a n/a n/a yes n/a n/a

47 m senior 21-24 Marketing 2.41-2.80 no less no no 0 0


49 m junior 17-20 Management 2.81-3.20 yes n/a no yes 1 to 3 <1


51 f senior 21-24 ssm 2.41-2.80 no less no no 0 0


53 m freshman 29-32 Bussiness 3.21-3.60 no less no no 0 0


55 m junior 21-24 Bussiness 3.21-3.60 no less and none no no 0 0

56 m senior 21-24 Bussiness 3.21-3.60 no less no no 0 0

57 m junior 21-24 Finance 2.81-3.20 yes depends n/a no 0 0

58 m junior 21-24 ssm 3.21-3.60 yes none yes yes 1 to 3 3 to 10

59 m senior 21-24 Marketing 3.21-3.60 yes less no no 0 0

60 m senior >40 Management 2.81-3.20 no less no no 0 0

61 m junior 21-24 Finance >3.6 no none no no 0 0

62 m junior 17-20 Management 3.21-3.60 no less no no 0 0

63 f freshman 17-20 Literature 3.21-3.60 no less yes no 0 0

64 m junior 21-24 Accounting 3.21-3.60 yes less no no 0 0

65 m sophomore 17-20 Bussiness 2.41-2.80 no none yes yes 1 to 3 1 to 3

66 m junior 17-20 Psychology 2.41-2.80 no less no no 0 0

67 m sophomore 17-20 PSCI 3.21-3.60 yes none yes no 0 0

68 m junior 25-28 Management 2.81-3.20 no none yes yes 1 to 3 3 to 10

69 f freshman 17-20 n/a 3.21-3.60 yes less no no 0 0

70 f senior 29-32 Accounting n/a no less no no 0 0

71 f senior 25-28 Nursing 3.21-3.60 no less no no 0 0

72 m junior 21-24 Bio 3.21-3.60 no less yes no 0 0

73 m senior 21-24 Information sys 2.81-3.20 yes less no no 0 0

74 m junior 21-24 Accounting 3.21-3.60 no none yes no 0 0

75 F Junior 17-20 Accounting 2.41-2.8 No less No yes n/a 1

76 F junior 21-24 Human Development 3.21-3.60 yes less NO no 0 0

77 F senior >40 Chimistry 3.21-3.60 no less No no 0 0

78 M junior 29-32 Management 3.21-3.60 yes less NO no 0 0

79 F junior 21-24 n/a 2.41-2.80 no less NO NO 0 0

CSUSM 9

80 F junior 21-24 Finance >3.6 yes less No No 0 0

81 M junior 21-24 Business 3.21-3.60 yes less No No 0 0

82 F Senior 25-28 Liberal studies 2.01-2.4 yes no Impact yes yes >10 >10

83 F junior 21-24 History >3.6 yes More attractive No no 0 0

84 F senior 25-28 Management 3.21-3.60 no LESS NO NO 0 0

85 F junior 21-24 Marketing 3.81-3.20 yes less yes no 0 0

86 F junior 21-24 Management >3.6 no less NO NO 0 0

87 M senior 21-24 Management 2.41-2.8 no no Impact no No 0 0

88 F senior 21-24 Management 3.21-3.60 yes less NO NO 0 0

89 F senior 21-24 Management 3.81-3.20 yes no Impact yes yes 4 to 6 1 to 3

90 M senior >40 Business 3.21-3.20 yes less NO NO 0 0

91 F junior 21-24 Management >3.6 yes less NO NO 0 0

92 F junior 21-24 Business 3.21-3.60 NO LESS NO NO 0 0

93 M senior 25-28 HTM >3.6 no less NO NO 0 0

94 M senior 37-40 Management 3.21-3.60 yes no Impact YES YES >10 3 to 10

95 F senior 25-28 Management 3.21-3.60 YES less YES NO 0 0

96 M junior 21-24 Business 2.81-3.20 yes no Impact NO NO 0 0

97 M junior 25-28 Finance 2.81-3.20 yes less NO NO 0 0

98 M senior 21-24 Finance 3.81-3.20 no less yes NO 0 0

99 M junior 21-24 Finance 3.21-3.60 yes less NO NO 0 0

100 M junior 21-24 Management 2.41-2.80 yes no Impact yes no 0 0

101 F junior >40 N/A 3.21-3.60 YES less NO NO 0 0

102 F senior 39-32 Finance 3.21-3.60 yes less NO NO 0 0

103 F junior 21-24 Management 2.41-2.80 no less NO NO 0 0

104 M junior 21-24 HTM 3.21-3.60 yes less NO yes 4 to 6 <1

105 M senior 21-24 Business 2.81-3.20 no less NO NO 0 0

CSUSM 10

Frequency Distribution of Age

Mean Standard Deviation and Frequency Mean Standard Deviation and Frequency

In the histogram above pertaining to the smoking sample, most of the smokers are in the

younger range between ages 17 and 24. The mean is about 24 years old because of the outlier of

1 person being in the higher age range. The data shown above for the sample of non-smokers

illustrates most of the non-smoking students surveyed are between 21-24 years old. By

examining the graphical illustrations and comparing them to the actuall numberred data collected

Mean = 23.56666667

Standard Deviation = 5.548058433

CSUSM 11

it would indicate the majority of the students surveyed altogether were between the ages of 21

and 24. This would coincide with the facts that the majority of college students based on team

observations are between these same ages.

Frequency Distribution of GPA

Mean = 3.133317308


Mean = 3.163932584


Mean = 2.951666667


CSUSM 12

Out of our 105 sample, there are only 11 students who have above a 3.60 grade point

average. All of those students are non-smokers. The mean GPA is 3.16. The mean of the grade

point average for smoking students is slightly lower than the non-smoking students. Above a

3.60 GPA demonstrates great success as a student, the fact our data shows them all as non-

smokers is evidence against smoking as a student. The relationship between smoking and GPA

was our team’s largest concern. The data is illustrated in bar graphs to show the variations.

The mean for cigarettes per day was determined by using midpoints. The mean is about 5

cigarettes per day. The mean for years smoking is 3.4. There aren’t too many students who have

been smoking over 10 years possibly because they are still young and have not lived long enough

to smoke for over 10 years. In addition given their young adult status their smoking habit remain

socially based and lacks the dependent stage such as in a chain smoker at a later age, this would

give reason for the greater number of smokers with the fewest number of cigarettes a day.

Mean = 4.769230769


Mean = 3.4


CSUSM 13

About half of the non-smoking students have a family history of smoking. This

information could mean that students who do have a family history of smoking are trying to

CSUSM 14

avoid it because they see smoking in the home first hand. It could also mean that students who

have no family history of smoking are raised that way. Out of the smoking students, 10 have a

family history of smoking while 4 do not. This could possibly be a factor for the smoker. The smoking

lifestyle of acceptance exists in the smokers, our data indicates this. As small of a sample as ours is the

compare and contrast of the numbers stills exists.

CSUSM 15

None of the smokers find smoking to be more attractive; but there are 3 smokers who

find it less attractive. 10 students say that there is no impact on attractiveness. There was only 1

student who finds smoking more attractive. Most of the students find smoking less attractive.

The only person who finds smoking more attractive is a non-smoker. This is very interesting

CSUSM 16

because it is not expected. But as a team we analyze this data to mean that smoking has very

little to do with attractiveness from a dating perspective and visa versa.

CSUSM 17

Out of the 15 smoking students, 11 said that they would date a smoker and a surprising 3

students said they would not date a smoker. This is really interesting considering that the 3

students are smokers themselves. Out of 25 students who would date a smoker, 14 of them are

non-smokers. The majority of smokers would not date smoker.

The sample consists of 105 students; out of the 105, only 15 students are smokers. To

find the mean and standard deviation, the midpoints were used because our survey had ordinal

data. The mean and standard deviation is not shown on the pie charts where it is not necessary.

Some of the histograms do not add up to the correct total of sample data because there was no

answer from the survey. However, we did not throw out the entire survey; instead used all of the

information that was available.

CSUSM 18

Conditional Probabilities Relating to Data Collected

Probability Rule 4: Addition Rule for Any Two Events, E1 and E2 P(E1 or

E2)=P(E1)+P(E2)-P(E1 and E2).

Table 1. Smoker Nonsmoker Male 11 51 Total 105 Female 4 39 Table 2. GPA>3.0 GPA<3.0 Smoking Male 7 4 Total 15 Smokers Smoking Female 2 2

Graphical Representation

CSUSM 19

Table 3. GPA>3.0 GPA<3.0 Total 90 Nonsmokers Nonsmoking Male 38 13 51 Males

Nonsmoking Female 30 939 Females

The table and graphical representation shows an almost even result on both female and male ends, however there is a small difference and improvement in the male smoking GPA compared to the female’s GPA. Table 4. Age > 20 Age ≤20 Total 105 Male 51 11 62 Males Female 33 10 43 Females Table 5.

Age > 20 Age ≤20 Total 15

Male Smokers 8 3 11 Males Smokers

Female Smokers 2 2 4 Females Smokers

Probability Calculations

Event 1= Male

CSUSM 20

P(E1)=62/105 0.590476 Event 2= Female 0.409524 P(E2)=43/105 P(E1 or E2)=P(E1)+P(E2)‐P(E1 and E2) .590476+.409524‐0=1.0 Probability of Either a Male or Female 100% P(E1 and E2) 11/105=.10476 Probability of Male and Smoker Event 1= Male P(E1)=62/105 0.590476 Event 2=Smoker P(E2)=15/105 0.142857 P(E1 or E2)=P(E1)+P(E2)‐P(E1 and E2) 34.2% .590476+.142857‐.10476= 0.342859 Probability of Either Male or Smoker

P(E1 and E2) 4/105=.0380 Probability of Female and Smoker

Event 1= Female P(E1)=43/105 0.409524

Event 2=Smoker P(E2)=15/105 0.142857 14.2%

P(E1 or E2)=P(E1)+P(E2)‐P(E1 and E2) .409524+.142857‐.0380= 0.514381 Probability of Either Female or Smoker

P(E1 and E2) 51/105=.4857 Probability of Male and Nonsmoker

Event 1= Male P(E1)=62/105 .5905 Probability

Event 2=Non‐smoker

P(E2)=90/105 .857 Probability P(E1 or E2)=P(E1)+P(E2)‐P(E1 and E2) 96.18%

.5905+.857‐.4857= 0.9618 Probability of Either Male or Nonsmoker

P(E1 and E2) 39/105=.3714 Probability of Female and Nonsmoker

CSUSM 21

Event 1= Female P(E1)=43/105 0.409524 Probability

Event 2=Nonsmoker P(E2)=90/105 0.857 Probability

P(E1 or E2)=P(E1)+P(E2)‐P(E1 and E2) 89.5% .409524+.857‐.3714= 0.895124 Probability of Either Female or Nonsmoker

We see a dominant probability in locating a male or nonsmoking candidate the reason being is based on our set of data the dominant characteristics were male people and or nonsmokers.

Event 1= Male P(E1)=62/105 .5905 Probability

Event 2= GPA > 3.0 P(E2)=77/105 .73333 Probability

P(E1 and E2) 42.8% 45/105=.42857 Probability of Male and GPA > 3.0

Event 1= Female P(E1)=43/105 0.409524


P(E1 and E2) 30.5% 32/105=.30476 Probability of Female and GPA > 3.0

Event 1= Male Smoker 11/105=.10476 Probability of Male and Smoker


P(E1 and E2) 7% 7/105=.066667 Probability of Male Smoker and GPA > 3.0 Event 1= Female Smoker

4/105=.0380 Probability of Female and Smoker Event 2= GPA > 3.0

P(E2)=77/105 .73333 Probability

P(E1 and E2) 2%

CSUSM 22

2/105=.0190 Probability of Female Smoker and GPA > 3.0 Our team sought it necessary to develop the critical conditional probability sequences that we thought most impacted our question of research. Because the sample of smokers collected is in such low standard compared to the greater population the conditional probabilities are lower as well. For instance both female gender and GPA>3.0 are two of the fewest occurring events therefore when a event1 and event 2 probability is set up the lowest percentage of occurrence is the result.

Event 1= Male Nonsmoker 51/105=.4857 Probability of Male and Nonsmoker


P(E1 and E2) 36.2% 38/105=.3619 Probability of Male Nonsmoker and GPA > 3.0 Event 1= Female Nonsmoker

39/105=.3714 Probability of Female and Nonsmoker Event 2= GPA > 3.0

P(E2)=77/105 .73333 Probability

P(E1 and E2) 28.6% 30/105=.2857 Probability of Female Nonsmoker and GPA > 3.0

Probability Rule 5: Addition Rule for Mutually Exclusive Events

Two Mutually Exclusive Events E1 and E2

Binomial Formula

n= Random Sample Size 30 person Sample

E1 E2

P(x)n

x ! n x

p q

x n x !

( ) ! =

−

−

CSUSM 23

x= Number of successes n‐x= Number of Failures p= probability of a success 0.14285714 q=1‐p = Probability of a failure 0.85714286 n!=n(n‐1)(n‐2)(n‐3)…1 0!=1 by definition P(x)= 30! (.14285714) power of 4(.85714286) power of 26 4!(30‐4)! 4.16E‐04 0.0181712

100% Probability of encountering a smoker in a 30 person sample from the population.

Correlation t-Tests

Hypothesis:

Non-smoking average G.P.A. > 3.00

Smoking average G.P.A < 3.00 and

Non-smoking – smoking > 0

t Test for Differences in Two Means

Data Hypothesized Difference 3Level of Significance 0.05

Population 1 Sample Sample Size 105Sample Mean 3.16Sample Standard Deviation 0.365


Intermediate Calculations Population 1 Sample Degrees of Freedom 104Population 2 Sample Degrees of Freedom 104Total Degrees of Freedom 208Pooled Variance 0.145021Difference in Sample Means 0.21t Test Statistic -53.0847

CSUSM 24

Since the requirement level of significance α =0.05, we reject Ho only when the sample mean is

less than 5% into the range, thus we do not declare the Hypothesis Ho wrong unless the sample

data strongly indicates this is wrong, in other words we do not declare that HA true unless the

sample data strongly indicates that is true.

This two tailed test for the difference in two means uses the sample size of 105 for both sample 1

and sample two. Using a level of significance of 0.05.

Hypothesis:




Based on the data we reject the null hypothesis; there is no evidence that suggests a higher

overall average G.P.A. among non-smokers vs. smokers





Two-Tail Test

Lower Critical Value -1.97143Upper Critical Value 1.971435p-Value 6.7E-123

Reject the null hypothesis

CSUSM 25

Intermediate Calculations Population 1 Sample Degrees of Freedom 88Population 2 Sample Degrees of Freedom 14Total Degrees of Freedom 102Pooled Variance 0.136463Difference in Sample Means 0.21t Test Statistic -27.0596

Two-Tail Test Lower Critical Value -1.9835Upper Critical Value 1.983495p-Value 2.39E-48

Reject the null hypothesis This two tailed test for the difference in Two means uses the sample size of 89 for sample 1

(non-smokers) and a sample size of 15 for sample 2 (smokers). Using a level of significance of

0.05.

Hypothesis:




Based on the data we reject the null hypothesis; this indicates that there is not a difference of

3.00 among the two samples





CSUSM 26

Intermediate Calculations Population 1 Sample Degrees of Freedom 88Population 2 Sample Degrees of Freedom 14Total Degrees of Freedom 102Pooled Variance 0.136463Difference in Sample Means 0.21t Test Statistic 2.036741

Two-Tail Test Lower Critical Value -1.9835Upper Critical Value 1.983495p-Value 0.044267

Reject the null hypothesis

Hypothesis: H0: non-smokers – smokers ≤ 0.0

H1: non-smokers – smokers > 0.0

The test shown here proves there is a difference between non-smokers and smokers G.P.A. and

the indicated sample mean for the two samples suggests that non-smokers have a higher overall

G.P.A. than smokers. Non-smokers sample mean G.P.A. 3.16, Smoker sample mean G.P.A.

2.95.

This also can be due to the fact that out of 105 surveys conducted that only 15 where smokers

and 89 where non-smokers hence the chances to correctly correlate the G.P.A. between the two

have been skewed.

CORRELATION

Column 1 Column 2

Column 1 1

Column 2 ‐0.57224 1

This is the output of the correlation between non-smokers (89) and smokers (15)

CSUSM 27

There is a negative correlation between non-smokers and smokers meaning that the G.P.A. is

lower among the smokers than the non-smokers.

AGE TOTAL AGE (NON‐SMOKING) AGE (SMOKING) GPA (Total)

GPA (NON‐SMOKING) GPA (SMOKING)

AGE TOTAL 1

AGE (NON‐SMOKING) 1 1

AGE (SMOKING) ‐0.668417667 ‐0.668417667 1

GPA (Total) 0.600557338 0.607914202 ‐0.691636195 1

GPA (NON‐SMOKING) 0.607914202 0.607914202 ‐0.691636195 1 1

GPA (SMOKING) ‐0.788263423 ‐0.788263423 0.599683101 ‐0.5722359 ‐0.572235919 1

This is the correlation between all relevant sample data. Surveys that had marks (n/a) where

replaced with a zero there by possibly skewing the data slightly. There were only four surveys

that had to be adjusted with a zero.

CSUSM 28

The lowest data point is at 2.2 and with the smokers the trend line is steep meaning it is possible

for smokers to have a high G.P.A. if there are a lot of smokers on campus, but the data we have

collected with only 15 out of 105 (14.3%) students shows that the collective G.P.A. is still lower

than that of the none smokers. This data is contradictory with a correlation of .758 in regards to

smokers obtaining high G.P.A. compared to the non-smokers. It is diffcult to concretely deduce

that the smoking GPA is lower than the non-smoking GPA based on our one sample. The shows

the possibility of earning a higher GPA as a smoker, particularly the probability of doing so in a

large crowd of smokers.

CSUSM 29

Non-smokers are the majority of our data and therefore the correlation seems to flatten out with

only a .165 trend of not smoking in relation to their G.P.A. Below the 1 marker the data remains

very low in correlation, this is a result that we expected simply from observing the data as a

team.

CSUSM 30

This is a direct comparison of smokers and non-smokers and as you can see the lack of sample

data to correctly measure the G.P.A. is consistent with the smoker’s trend line telling us that

over time with more data collected smokers will have a higher average G.P.A. We do not know

this for sure.

Conclusions and Implications

Based on our survey, there is no strong correlation coefficient among students who

smoke or who are non-smokers, therefore we can not prove any sort of assumption about the

smoking habit. The only reason students smoke is related to their family history and their ages,

the younger their age the more they get addicted to the social activity. The small survey and

study performed by our team could provide evidence to support a negative argument between

GPA and smoking, however the comparison shows minimul significance and therefore neutral in

the best standards. There could be claim that the smoking habit has an affect on GPA; our data

indicates that the GPA of students who smoke are lower (2.9) compared to non-smokers (3.16).

In order to restrict the smoking habit of students at California State University San

Marcos we need to tighten the smoking policy so that the student only light up in the campus

parking lots such as lots J, K, L, N, O, X, Y, and Z. The reason we are asking for these lots is

because the smoking designated areas are not in favorable places, they are located at the

computer labs, outside of classrooms, and near walkways as an example the business building

designates a smoking area directly outside. Based on observation and intuitiveness students are

perturbed when they are forced to pass through second hand smoke to reach a classroom. Our

team believes this is a major problem for the students and we also encourage CSUSM to restrict

smoking in school and by doing this it will not only increase the value of education but also help

students to get rid of the smoking habit. The external factors of smoking such as health risks and

CSUSM 31

annoyance has been proven to have a correlation, therefore our suggestion although are not

concretely backed up by our study are backed up by facts.

Documents

California State University San Marcos Smoking & GPA Analysispublic.csusm.edu/fangfang/Teaching/BUS304/Team... · 2008-05-19 · The following data was compiled over a multiple week