Ba 319 final presentation last edits
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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.
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 =
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?