Ba 319 final presentation last edits

BA 319 – STATISTICSFINAL PRESENTATION

By: Majed Alsalhi

Osama Hameed

Sary Abu Nijem

Todd Garey

Introduction

In today’s business environment, the ability to prove effectiveness and maximize the return of online marketing efforts at each step of the planning, execution and evaluation process is a necessity, and the ability to benchmark your campaign efforts by reviewing delivery against your goals is crucial.

Whether driving traffic to a content website or marketing products and services through the Internet, successful marketers require superior consumer insight to help them design successful marketing strategies, minimize risk and maximize revenue.

Introduction

According to ComScore’s Ad Metrix data, social networking sites such as Facebook and Twitter hosted 13.8 billion online advertising impressions in August this year.

Over 25% of the advertising market online.

Introduction

eMarketer estimates of revenue from 2009 to 2011, expressed in billions of dollars (including year-over-year percentage gain).

Facebook's U.S. and international ad sales are the biggest driver of growth. 

Credit: eMarketer

Introduction

Earned media takes center stage.  Marketers will look for better ways to

manage and measure the impact of earned media.

The additional free exposure that a brand gets when consumers talk about a brand online or share information about their interactions with it.

Introduction

Social combined with search will yield better results and more ad opportunities. 

Search will meet social by incorporating real-time content (e.g., tweets from Twitter and status updates from MySpace and Facebook) into search results, adding information from social network friends to search results, and using collective information from other Web users to hone search relevancy. These trends will yield new ad formats—and will raise new red flags for privacy advocates.

Introduction

• Current statistics showing how much those online advertisement are spending on different

kind of social network websites.

Social ad networks will expand. Expect more momentum behind advertising that is targeted based on information from social network user profiles.

Introduction

Some social networking websites clearly do work, in the sense that they attract significant traffic.

Users become dedicated and loyal, working with or playing with the website frequently, and even forming lasting friendships with other user.

Advertising in those social network website have a huge impact.

Introduction

Hypothesis(es);

Does advertising online impact the perception of those products/services on different genders?

Social Network Advertising; Annoying or Effective?

Will this new trend will catch more attention than the traditional advertisement?

Target Audience

College students who have a social networking website

Facebook Myspace Twitter

Sampling Plan

We collected 8 one-on-one interviews We also collected at least 45 online

questionnaires.

Method of Survey Administration

Our one-on-one interviews were personal interviews

Our online questionnaire was performed by making a survey at surveymonkey.com

Summary of Respondents

Online questionnaire asked 8 questions What is your gender? What is your level of education? What is your favorite networking website? How many hours per day do you spend on social

networking websites? Do you pay attention to social networking websites? Have you ever clicked on an ad from a social

networking website? Have you ever purchased a product/service from an ad

on a social networking website? In your opinion, how effective is advertising on a social

networking website

Summary of Respondents

One-on-one interviews asked 3 questions Has an advertisement on a social

networking website ever caught your attention? If so what was the service/product?

Has social media become overly addicting? Why or why not?

Do you feel that advertisers take advantage of your demographic information and target their ads appropriately?

Statistics

What is your favorite social networking website?

Statistics

Have you ever clicked on the advertisement of a service/product on a social networking website?

Statistics

Have you ever purchased a service/product from an advertisement that you clicked on?

Yes

No

0 2 4 6 8 10 12 14

Statistics

How many hours per day do Males spend on social networking websites?

Two Sample Proportion Test

HYPOTHESIS TESTS x-value sample 1 - 17 x-value sample 2 - 10

proportion 1 - 54.8% proportion 2 - 90.9% pooled proportion = 0.643 sample size 1 - 31 sample

size 2 -11Males Females

std error = 0.168

Does gender effect how often someone pays attention to advertisements on social networking websites?

NULL: p >= p2 Gender does NOT effect how often someone pays attention to advertisements on social networking websites

ALTERNATIVE: p1<p2 Gender does effect how often someone pays attention to advertisements on social networking websites

Two Sample Proportion Test

one-tailed or two tailed?

test statistic (obs) = (2.145)

critical measure = 1.645

|obs| > critical? Yes

p-value = 0.02

a-level = 0.050

p-value < a-level? Yes

Reject the NULL, gender does effect how often someone pays attention to advertisements on social networking websites

Questions To Be Answer

Does gender has an effect on social media? Does level of education has an impact

toward social media? Do certain gender has a favorite networking

website? Does advertisements effect gender on the

social networking websites? Does gender influence purchasing a

service/product from an advertisement on social websites ?

Hypotheses Test (Two Sample Mean)

HYPOTHESIS TESTS sample mean 1 1.12 stdev 1 333.2%

pooled sample stdev 3.469 sample size 1 42

std error 0.757 sample mean 2 2.32 stdev 2 360.1%

Does Gender has a favorite networking website?   sample size 2 42

NULL: u1 <= u2 GenderDoes Have a favorite social networking site ?      

ALTERNATIVE: u1 > u2

Gender Does Not have a fovorite social networking site ?      

one-tailed or two tailed? 1 enter only 1 or 2

type of test? t testenter only z or t

test statistic (obs) (0.053)critical measure 0.829 degrees of freedom 82

|obs| > critical?? NO

p-value 0.479

a-level 0.050

←enter alpha level here  

p-value < a-level?? NO NULL is Accepted

Gender Effect on Social Websites

1=male 0=female Facebook vs.

Twitter

0 10

5

10

15

20

25

30

35

40Total

Total

Hypotheses Test (One Sample Proportions)

HYPOTHESIS TESTSsample

proportion 2.90

population proportion 0.75

std error 0.0668153

sample size 42

Does level of education impact social media ?       

NULL: < .75ulevel of education does not impact social media      

ALTERNATIVE: >= .75ulevel of education does impact social media      

one-tailed or two-tailed? 1

test statistic (obs) 32.25

critical measure 0.83

obs > critical? YES

p-value 0.00000

a-level 0.05

p-value < a-level? YES REJECT NULL

Impact of Level of Education

0 10

10

20

30

40

50

60

70

80

90

100

Level of

Education

0 = Female 1 = Male

Hypotheses Test (One Sample Mean)HYPOTHESIS TESTS sample mean 0.74

population mean 0.75refrence value

stdev 67.02

sample size 42

does Gender has an effect on social media ?       

NULL: <= 180.06u

Gender DOES efect social media      

ALTERNATIVE: > 180.06u

Gender DOES NOT effect social media      

one-tailed or two-tailed? 1

test statistic (obs) 0.00

critical measure 1.68 degrees of freedom 41

|obs| > critical? NO

p-value 0.50

a-level 0.05

p-value < a-level? NO

DO NOT REJECT NULL

Hypotheses Test (Two Sample Mean)

HYPOTHESIS TESTS sample mean 1 1.88

stdev 1 333.2%

pooled sample stdev 3.469 sample size 1 42

std error 0.757 sample mean 2 1.31

stdev 2 360.1%Does Gender influence purchasing a service/product from an advertisement on social websites ? sample size 2 42

NULL: 1 <= 2 u u

Gender DOES impact purchasing a service/product from an advertisement on websites      

ALTERNATIVE: 1 > 2 u u

Gender DOES NOT impact purchasing a service/product from an advertisement on websites      

one-tailed or two tailed? 1enter only 1 or 2

type of test? t test

enter only z or t

test statistic (obs) (0.035)

critical measure 0.829degrees of freedom 82

|obs| > critical?? NO

p-value 0.486

a-level 0.050 ←enter alpha level here  

p-value < a-level?? NO ACCEPT THE NULL

Influence on Gender on Buying Product/Service

76% males 24%females

24%

76%

Total

0 1

Hypotheses Test(Two Sample Proportions)

HYPOTHESIS TESTSx-value sample

1 2.3571 x-value sample 2 1.5476

for the proportion proportion 1 5.6% proportion 2 3.7%

pooled proportion 0.046 sample size 1 42 sample size 2 42

std error 0.046

Does advertisements effect Gender on the social networking websites?

NULL: 1 > 2p pAdvertisement DOES effect Gender on social websites

ALTERNATIVE: 1 <= 2p pAdvertisement DOES NOT effect Gender on social websites

one-tailed or two tailed? 1enter 1 or 2

above

test statistic (obs) 0.420

critical measure 1.645

|obs| > critical?? No

p-value 0.34

a-level 0.050

←enter alpha level here   ACCEPT NULL

p-value < a-level?? NO

Effect of Advertisement on Gender in Social Websites

25% Female 75% males

25%

75%

Total

01

Data Table

Gender 0 = Female1= Male

Level of Education 1 = Freshmen2 = Sophomore

3 = Junior4 = Senior

Favorite Networking Websites 1 = Facebook2 = Twitter

Hours Spent on Social Network Sties Hours (1, 2, 3, …, 10)

Attention Paid to Advertisement on Social Networking Sites 1 = Always2 = Sometimes

3 = Never

Effectiveness of Advertisement on Social Networking Sites 1 = Very2 = Sometimes3 = Not at All

Gender Influence Purchasing a Service/product from an advertisement on social websites?

1= Yes 2= No

Chart # 1

0 10

10

20

30

40

50

60

70

80

90

100

Level of

Education

0 = Female 1 = Male

Scatter Plot

0 0.2 0.4 0.6 0.8 1 1.20

0.5

1

1.5

2

2.5

3

3.5

4

4.5

level of education?Linear ( level of education?)

0 = Female 1 = Male

1=

Fre

shm

en

2 =

Sophm

or

3 =

Junio

r4 =

Senio

r

Scatter Plot

0 0.2 0.4 0.6 0.8 1 1.20

0.5

1

1.5

2

2.5

3

3.5

favorite networking website?Linear (favorite networking website?)

0 = Female 1 = Male

1 =

Facebook

2 =

Tw

itte

r

Scatter Plot

0 0.2 0.4 0.6 0.8 1 1.20

2

4

6

8

10

12

hours spent on networking websites?Linear (hours spent on networking websites?)

0 = Female 1 = Male

Hours

Spent

on S

ocia

l N

etw

ork

Sit

es

Scatter Plot

0 0.2 0.4 0.6 0.8 1 1.20

0.5

1

1.5

2

2.5

Does Gender influence purchasing a service/product from an adver-tisement on social websites ?Linear (Does Gender influence purchasing a service/product from an advertisement on social web-sites ?)

0 = Female 1 = Male

1 =

YES

2 =

No

Regression Analysis

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.046521441

R Square 0.002164245Adjusted R Square -0.022781649

Standard Error 0.450040999

Observations 42

ANOVA

  df SS MS FSignificance

F

Regression 1 0.017571604 0.017571604 0.086757545 0.769863723

Residual 40 8.101476015 0.2025369

Total 41 8.119047619     

  CoefficientsStandard

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 0.684501845 0.194753583 3.514707318 0.001109902 0.290890174 1.078113516 0.290890174 1.078113516 level of education? 0.018450185 0.062639327 0.294546338 0.769863723 -0.108148617 0.145048986 -0.108148617 0.145048986

Correlation between (Gender & Level of Education)

Regression Analysis

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.042922996

R Square 0.001842384

Adjusted R Square -0.023111557

Standard Error 0.450113575

Observations 42

ANOVA

  df SS MS F Significance F

Regression 1 0.0149584 0.0149584 0.073831367 0.787235425

Residual 40 8.104089219 0.20260223

Total 41 8.119047619     

  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 0.68401487 0.210800665 3.244842085 0.002377053 0.257970838 1.110058902 0.257970838 1.110058902favorite networking website? 0.048327138 0.177856858 0.271719281 0.787235425 -0.311134978 0.407789253 -0.311134978 0.407789253

Correlation between (Gender & Hours Spent Online on Social Network Websites)

Regression Analysis

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.077116908R Square 0.005947017

Adjusted R Square-

0.018904307Standard Error 0.449187141Observations 42

ANOVA

  df SS MS FSignificance

F

Regression 1 0.048284118 0.048284118 0.239303843 0.627381191

Residual 40 8.070763501 0.201769088

Total 41 8.119047619     

  CoefficientsStandard

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 0.610800745 0.269289132 2.268196789 0.028787981 0.066547113 1.155054377 0.066547113 1.155054377

effectivness of advertisment on a social networking website? 0.061452514 0.125621744 0.489186921 0.627381191 -0.192438498 0.315343526 -0.192438498 0.315343526

Correlation between (Gender & Effectiveness of Advertisement on

Social Network Sites)

Regression Analysis

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.282680138

R Square 0.079908061

Adjusted R Square 0.056905762

Standard Error 0.432153626

Observations 42

ANOVA

  df SS MS F Significance F

Regression 1 0.648777349 0.648777349 3.473916339 0.069695435

Residual 40 7.47027027 0.186756757

Total 41 8.119047619     

  CoefficientsStandard

Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 0.016216216 0.393004943 0.041262118 0.967292209 -0.778076395 0.810508827 -0.778076395 0.810508827

Does Gender influence purchasing a service/product from an advertisement on social websites ? 0.383783784 0.205909765 1.863844505 0.069695435 -0.03237537 0.799942938 -0.03237537 0.799942938

Correlation between (Gender & If It Influence the Purchase of Products or Service from Social Network

Sites)

Conclusion

Relevant findings: Social networking websites hosted13.8 billion online

advertising impressions in August this year alone Facebook is the leader in advertising, they spent

$850 million and accounted for 54% of all advertising among social networking websites

Males pay less attention to advertisements than females

Individuals can spend up to 10 hours per day on facebook

17 of 45 individuals who have a social networking website, click on an ad

Conclusion

Impact of our findings: Our findings prove that social networking

websites attract significant traffic Facebook is clearly ahead of the rest of the

pack when it comes to social networking website advertising

Myspace decreased its advertisement in the U.S. by 23% last year

Of the 17 individuals who clicked on an ad from a social networking website, 4 purchased the product of service

Conclusion

Suggestions for improving this study: We suggest companies should increase

advertising on Facebook and decrease advertising on Myspace

Advertisements should be directed more towards females because they are much more likely to pay attention to the ads

Questions?