SlideShare a Scribd company logo
1 of 108
Frequency Distribution,  Cross-Tabulation,  and Hypothesis Testing
Chapter Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Chapter Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Chapter Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Chapter Outline ,[object Object],[object Object],[object Object],[object Object]
Internet Usage Data Respondent  Sex  Familiarity  Internet  Attitude Toward  Usage of Internet Number   Usage Internet Technology  Shopping  Banking   1   1.00   7.00   14.00 7.00   6.00   1.00 1.00 2   2.00   2.00   2.00 3.00   3.00   2.00 2.00 3   2.00   3.00   3.00 4.00   3.00   1.00 2.00 4   2.00   3.00   3.00 7.00   5.00   1.00 2.00  5   1.00   7.00   13.00 7.00   7.00   1.00 1.00 6   2.00   4.00   6.00 5.00   4.00   1.00 2.00 7   2.00   2.00   2.00 4.00   5.00   2.00 2.00 8   2.00   3.00   6.00 5.00   4.00   2.00 2.00 9   2.00   3.00   6.00 6.00   4.00   1.00 2.00 10   1.00   9.00   15.00 7.00   6.00   1.00 2.00 11   2.00   4.00   3.00 4.00   3.00   2.00 2.00 12   2.00   5.00   4.00 6.00   4.00   2.00 2.00 13   1.00   6.00   9.00 6.00   5.00   2.00 1.00 14   1.00   6.00   8.00 3.00   2.00   2.00 2.00 15   1.00   6.00   5.00 5.00   4.00   1.00 2.00 16   2.00   4.00   3.00 4.00   3.00   2.00 2.00 17   1.00   6.00   9.00 5.00   3.00   1.00 1.00 18   1.00   4.00   4.00 5.00   4.00   1.00 2.00 19   1.00   7.00   14.00 6.00   6.00   1.00 1.00 20   2.00   6.00   6.00 6.00   4.00   2.00 2.00 21   1.00   6.00   9.00 4.00   2.00   2.00 2.00 22   1.00   5.00   5.00 5.00   4.00   2.00 1.00 23   2.00   3.00   2.00 4.00   2.00   2.00 2.00 24   1.00   7.00   15.00 6.00   6.00   1.00 1.00 25   2.00   6.00   6.00 5.00   3.00   1.00 2.00 26   1.00   6.00   13.00 6.00   6.00   1.00 1.00 27   2.00   5.00   4.00 5.00   5.00   1.00 1.00 28   2.00   4.00   2.00 3.00   2.00   2.00 2.00  29   1.00   4.00   4.00 5.00   3.00   1.00 2.00 30   1.00   3.00   3.00 7.00   5.00   1.00 2.00 Table 15.1
Frequency Distribution ,[object Object],[object Object]
Frequency Distribution of Familiarity with the Internet Table 15.2
Frequency Histogram Figure 15.1 2 3 4 5 6 7 0 7 4 3 2 1 6 5 Frequency Familiarity 8
SPSS DATA ANALYSIS
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Statistics Associated with Frequency Distribution Measures of Location X = X i / n  i = 1 n X
[object Object],Statistics Associated with Frequency Distribution Measures of Location
[object Object],[object Object],Statistics Associated with Frequency Distribution Measures of Variability
[object Object],[object Object],[object Object],Statistics Associated with Frequency Distribution Measures of Variability s x = ( X i - X ) 2 n - 1   i = 1 n Sample,  not population
[object Object],[object Object],Statistics Associated with Frequency Distribution Measures of Shape
Skewness of a Distribution Figure 15.2 Skewed Distribution Symmetric Distribution Mean Median Mode (a) Mean Median Mode (b)
Steps Involved in Hypothesis Testing Fig. 15.3 Draw Marketing Research Conclusion Formulate H 0  and H 1 Select Appropriate Test Choose Level of Significance  Determine Probability Associated with Test Statistic Determine Critical Value of Test Statistic TSCR Determine if TSCR falls into (Non) Rejection Region Compare with Level of Significance,     Reject or Do not Reject H 0 Collect Data and Calculate Test Statistic
A General Procedure for Hypothesis Testing Step 1: Formulate the Hypothesis ,[object Object],[object Object],[object Object]
[object Object],[object Object],A General Procedure for Hypothesis Testing Step 1: Formulate the Hypothesis :  > 0 . 40 H 1
[object Object],A General Procedure for Hypothesis Testing Step 1: Formulate the Hypothesis H 0 :  = 0 . 4 0 :   0 . 4 0 Generally limited to production measures for Q.C. Purposes H 1
[object Object],[object Object],[object Object],A General Procedure for Hypothesis Testing Step 2: Select an Appropriate Test where
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],A General Procedure for Hypothesis Testing Step 3: Choose a Level of Significance
[object Object],[object Object],[object Object],[object Object],A General Procedure for Hypothesis Testing Step 3: Choose a Level of Significance
Probabilities of Type I & Type II Error Figure 15.4 99% of Total Area Critical Value of  Z   = 0.40    = 0.45    = 0.01 = 1.645 Z   = -2.33 Z    Z Z 95% of Total Area    = 0.05
Probability of z with a One-Tailed Test Unshaded Area  = 0.0301 Fig. 15.5 Shaded Area = 0.9699 z = 1.88 0
[object Object],[object Object],[object Object],A General Procedure for Hypothesis Testing Step 4: Collect Data and Calculate Test Statistic = = 0.089
A General Procedure for Hypothesis Testing Step 4: Collect Data and Calculate Test Statistic The test statistic  z  can be calculated as follows: =  0.567-0.40   0.089 = 1.88 In Words: “Our sample value was 1.88 Standard Deviations above our Hypothesized Mean Value How likely is it that actual population value is <.4? Our “hypothesized” population value (>.4) Our Sample Value  or Estimate: 17/30 Std Error Estimate 3.1% 2.5%
[object Object],[object Object],[object Object],[object Object],A General Procedure for Hypothesis Testing Step 5: Determine the Probability (Critical Value)
[object Object],[object Object],[object Object],A General Procedure for Hypothesis Testing Steps 6 & 7: Compare the Probability (Critical Value) and Making the Decision 
[object Object],[object Object],[object Object],A General Procedure for Hypothesis Testing Steps 6 & 7: Compare the Probability (Critical Value) and Making the Decision
[object Object],[object Object],A General Procedure for Hypothesis Testing Step 8: Marketing Research Conclusion
A Broad Classification of Hypothesis Tests Figure 15.6 Median/ Rankings Distributions Means Proportions Tests of Association Tests of Differences Hypothesis Tests
Cross-Tabulation ,[object Object],[object Object]
Gender and Internet Usage Table 15.3
Two Variables Cross-Tabulation ,[object Object],[object Object]
Internet Usage by Gender Table 15.4
Gender by Internet Usage Table 15.5
SPSS: CROSSTABS
CROSSTAB RESULTS CLARIFIED
CROSSTAB RESULTS Appears to be relationship between Gender and Internet Usage:  Is it  Significant ?
CROSSTAB SIGNIFICANCE There is  NO  statistical relationship between gender and internet usage at 5% Level! Must be >3.841 To Accept Alternative Hypothesis
Introduction of a Third Variable in Cross-Tabulation Fig. 15.7 Refined Association between the Two Variables No Association between the Two Variables No Change in the Initial Pattern Some Association between the Two Variables Some Association between the Two Variables No Association between the Two Variables Introduce a Third Variable Introduce a Third Variable Original Two Variables
[object Object],[object Object],[object Object],[object Object],[object Object],Three Variables Cross-Tabulation Refine an Initial Relationship
Purchase of Fashion Clothing by Marital Status Table 15.6
Purchase of Fashion Clothing by Marital Status Table 15.7
[object Object],[object Object],Three Variables Cross-Tabulation Initial Relationship was Spurious
Ownership of Expensive Automobiles by Education Level Table 15.8
Ownership of Expensive Automobiles by Education Level and Income Levels Table 15.9
[object Object],[object Object],[object Object],[object Object],Three Variables Cross-Tabulation Reveal Suppressed Association
Desire to Travel Abroad by Age Table 15.10
Desire to Travel Abroad by Age and Gender Table 15.11
[object Object],[object Object],Three Variables Cross-Tabulations No Change in Initial Relationship
Eating Frequently in Fast-Food  Restaurants by Family Size Table 15.12
Eating Frequently in Fast Food-Restaurants by Family Size & Income Table 15.13
[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Chi-Square
Chi-square Distribution Figure 15.8 Reject H 0 Do Not Reject H 0 Critical Value    2
Statistics Associated with Cross-Tabulation Chi-Square ,[object Object],[object Object],where n r = total number in the row n c   = total number in the column n = total sample size
[object Object],[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Chi-Square
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Chi-Square
[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Chi-Square
[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Phi Coefficient
[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Contingency Coefficient
[object Object],[object Object],Statistics Associated with Cross-Tabulation Cramer’s V
[object Object],[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Lambda Coefficient
[object Object],[object Object],[object Object],[object Object],Statistics Associated with Cross-Tabulation Other Statistics
Cross-Tabulation in Practice ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Hypothesis Testing Related to Differences ,[object Object],[object Object],[object Object],[object Object],[object Object]
A Classification of Hypothesis Testing Procedures for Examining Differences Fig. 15.9 Hypothesis Tests Independent Samples Paired Samples Independent Samples Paired Samples * Two-Group t test * Z test  * Paired t test * Chi-Square * Mann-Whitney * Median * K-S ,[object Object],[object Object],[object Object],[object Object],One Sample Two or More Samples One Sample Two or More Samples *  t test * Z test * Chi-Square * K-S  * Runs * Binomial Parametric Tests (Metric Tests) Non-parametric Tests (Nonmetric Tests)
Parametric Tests ,[object Object],[object Object],[object Object],[object Object]
Hypothesis Testing Using the t Statistic ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],Hypothesis Testing Using the t Statistic
[object Object],[object Object],[object Object],[object Object],[object Object],One Sample t Test H 0 :  <  4.0 > 4.0 =  = 1.579/5.385 = 0.293 t  = (4.724-4.0)/0.293 = 0.724/0.293 = 2.471 H 1 :
One Sample t Test 4.724 5.017 5.310 2.75% Probability
[object Object],[object Object],[object Object],[object Object],[object Object],One Sample t Test H 0 :  <  4.0 > 4.0 =  = 1.579/5.385 = 0.293 t  = (4.724-4.0)/0.293 = 0.724/0.293 = 2.471 H 1 :
[object Object],One Sample t Test
[object Object],[object Object],[object Object],[object Object],[object Object],One Sample z Test
One Sample z Test ,[object Object],[object Object]
Two Independent Samples Means ,[object Object]
Two Independent Samples Means ,[object Object]
Two Independent Samples Means ,[object Object],[object Object],2 ( ( 2 1 1 1 2 2 2 2 1 1 2 1 2 ) )           n n X X X X s n n i i i i or s 2 = ( n 1 - 1 ) s 1 2 + ( n 2 -1) s 2 2 n 1 + n 2 -2
[object Object],[object Object],[object Object],[object Object],Two Independent Samples Means
[object Object],[object Object],[object Object],[object Object],[object Object],Two Independent Samples F Test
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Two Independent Samples F Statistic
Two Independent-Samples  t  Tests Table 15.14 -
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Two Independent Samples Proportions
[object Object],[object Object],[object Object],[object Object],[object Object],Two Independent Samples Proportions
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Two Independent Samples Proportions
[object Object],Two Independent Samples Proportions
Paired Samples ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],Paired Samples
Paired-Samples  t  Test Number Standard Standard Variable of Cases Mean Deviation Error Internet Attitude 30 5.167 1.234 0.225 Technology Attitude 30 4.100 1.398 0.255 Difference = Internet  - Technology Difference Standard Standard 2 - tail t Degrees of 2 - tail Mean deviat ion error Correlation  prob. value freedom probability 1.067 0.828 0 .1511 0 .809 0 .000 7.059 29 0 .000 Table 15.15
Non-Parametric Tests ,[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Non-Parametric Tests One Sample K = M a x A i - O i
[object Object],[object Object],Non-Parametric Tests One Sample
K-S One-Sample Test for Normality of Internet Usage Table 15.16
[object Object],[object Object],[object Object],Non-Parametric Tests One Sample
[object Object],[object Object],[object Object],[object Object],[object Object],Non-Parametric Tests Two Independent Samples
[object Object],[object Object],[object Object],[object Object],Non-Parametric Tests Two Independent Samples
Mann-Whitney U - Wilcoxon Rank Sum W Test Internet Usage by Gender Table 15.17 Sex Mean Rank Cases Male 20.93 15 Female 10.07 15 Total 30 Corrected for ties U W z 2 - tailed  p 31.000 151.000 - 3.406 0.001 Note U = Mann - Whitney test statistic W = Wilcoxon W Statistic z = U transformed into a normally distributed  z stat istic.
[object Object],[object Object],[object Object],[object Object],Non-Parametric Tests Paired Samples
[object Object],[object Object],[object Object],Non-Parametric Tests Paired Samples
Wilcoxon Matched-Pairs Signed-Rank Test Internet with Technology Table 15.18
A Summary of Hypothesis Tests Related to Differences Table 15.19 Contd.
A Summary of Hypothesis Tests Related to Differences Table 15.19 cont.
SPSS Windows ,[object Object],[object Object],[object Object]
SPSS Windows ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],SPSS Windows
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],SPSS Windows

More Related Content

What's hot (19)

Aron chpt 11 ed (2)
Aron chpt 11 ed (2)Aron chpt 11 ed (2)
Aron chpt 11 ed (2)
 
Chi square test final
Chi square test finalChi square test final
Chi square test final
 
Z-Test with Examples
Z-Test with ExamplesZ-Test with Examples
Z-Test with Examples
 
Chisquare Test
Chisquare Test Chisquare Test
Chisquare Test
 
Chi Square Worked Example
Chi Square Worked ExampleChi Square Worked Example
Chi Square Worked Example
 
Chi square analysis
Chi square analysisChi square analysis
Chi square analysis
 
Chi square test
Chi square testChi square test
Chi square test
 
Chi‑square test
Chi‑square test Chi‑square test
Chi‑square test
 
Chi squared test
Chi squared testChi squared test
Chi squared test
 
Chi square Test
Chi square TestChi square Test
Chi square Test
 
The chi – square test
The chi – square testThe chi – square test
The chi – square test
 
Chi square
Chi squareChi square
Chi square
 
Test of significance
Test of significanceTest of significance
Test of significance
 
Hypothesis testing , T test , chi square test, z test
Hypothesis testing , T test , chi square test, z test Hypothesis testing , T test , chi square test, z test
Hypothesis testing , T test , chi square test, z test
 
Chi square
Chi squareChi square
Chi square
 
Statistical analysis for large sample
Statistical analysis for large sampleStatistical analysis for large sample
Statistical analysis for large sample
 
B.9 chi square
B.9 chi squareB.9 chi square
B.9 chi square
 
Chi square & related procedure
Chi square & related procedureChi square & related procedure
Chi square & related procedure
 
Small sample test
Small sample testSmall sample test
Small sample test
 

Similar to Freq distribution

Chapter 15 Marketing Research Malhotra
Chapter 15 Marketing Research MalhotraChapter 15 Marketing Research Malhotra
Chapter 15 Marketing Research MalhotraAADITYA TANTIA
 
Review & Hypothesis Testing
Review & Hypothesis TestingReview & Hypothesis Testing
Review & Hypothesis TestingSr Edith Bogue
 
250Lec5INFERENTIAL STATISTICS FOR RESEARC
250Lec5INFERENTIAL STATISTICS FOR RESEARC250Lec5INFERENTIAL STATISTICS FOR RESEARC
250Lec5INFERENTIAL STATISTICS FOR RESEARCLeaCamillePacle
 
Descriptive And Inferential Statistics for Nursing Research
Descriptive And Inferential Statistics for Nursing ResearchDescriptive And Inferential Statistics for Nursing Research
Descriptive And Inferential Statistics for Nursing Researchenamprofessor
 
Sampling_Distribution_stat_of_Mean_New.pptx
Sampling_Distribution_stat_of_Mean_New.pptxSampling_Distribution_stat_of_Mean_New.pptx
Sampling_Distribution_stat_of_Mean_New.pptxRajJirel
 
5_lectureslides.pptx
5_lectureslides.pptx5_lectureslides.pptx
5_lectureslides.pptxsuchita74
 
M.Ed Tcs 2 seminar ppt npc to submit
M.Ed Tcs 2 seminar ppt npc   to submitM.Ed Tcs 2 seminar ppt npc   to submit
M.Ed Tcs 2 seminar ppt npc to submitBINCYKMATHEW
 
Estimation in statistics
Estimation in statisticsEstimation in statistics
Estimation in statisticsRabea Jamal
 
ders 5 hypothesis testing.pptx
ders 5 hypothesis testing.pptxders 5 hypothesis testing.pptx
ders 5 hypothesis testing.pptxErgin Akalpler
 
A Lecture on Sample Size and Statistical Inference for Health Researchers
A Lecture on Sample Size and Statistical Inference for Health ResearchersA Lecture on Sample Size and Statistical Inference for Health Researchers
A Lecture on Sample Size and Statistical Inference for Health ResearchersDr Arindam Basu
 

Similar to Freq distribution (20)

Chapter 15 Marketing Research Malhotra
Chapter 15 Marketing Research MalhotraChapter 15 Marketing Research Malhotra
Chapter 15 Marketing Research Malhotra
 
Review & Hypothesis Testing
Review & Hypothesis TestingReview & Hypothesis Testing
Review & Hypothesis Testing
 
Ds vs Is discuss 3.1
Ds vs Is discuss 3.1Ds vs Is discuss 3.1
Ds vs Is discuss 3.1
 
250Lec5INFERENTIAL STATISTICS FOR RESEARC
250Lec5INFERENTIAL STATISTICS FOR RESEARC250Lec5INFERENTIAL STATISTICS FOR RESEARC
250Lec5INFERENTIAL STATISTICS FOR RESEARC
 
Descriptive And Inferential Statistics for Nursing Research
Descriptive And Inferential Statistics for Nursing ResearchDescriptive And Inferential Statistics for Nursing Research
Descriptive And Inferential Statistics for Nursing Research
 
Sampling_Distribution_stat_of_Mean_New.pptx
Sampling_Distribution_stat_of_Mean_New.pptxSampling_Distribution_stat_of_Mean_New.pptx
Sampling_Distribution_stat_of_Mean_New.pptx
 
Unit 3 Sampling
Unit 3 SamplingUnit 3 Sampling
Unit 3 Sampling
 
hypothesis.pptx
hypothesis.pptxhypothesis.pptx
hypothesis.pptx
 
5_lectureslides.pptx
5_lectureslides.pptx5_lectureslides.pptx
5_lectureslides.pptx
 
Descriptive Analysis.pptx
Descriptive Analysis.pptxDescriptive Analysis.pptx
Descriptive Analysis.pptx
 
T test
T test T test
T test
 
Basic statistics
Basic statisticsBasic statistics
Basic statistics
 
Descriptive Statistics
Descriptive StatisticsDescriptive Statistics
Descriptive Statistics
 
M.Ed Tcs 2 seminar ppt npc to submit
M.Ed Tcs 2 seminar ppt npc   to submitM.Ed Tcs 2 seminar ppt npc   to submit
M.Ed Tcs 2 seminar ppt npc to submit
 
Estimation in statistics
Estimation in statisticsEstimation in statistics
Estimation in statistics
 
Chapter_9.pptx
Chapter_9.pptxChapter_9.pptx
Chapter_9.pptx
 
ders 5 hypothesis testing.pptx
ders 5 hypothesis testing.pptxders 5 hypothesis testing.pptx
ders 5 hypothesis testing.pptx
 
DSE-2, ANALYTICAL METHODS.pptx
DSE-2, ANALYTICAL METHODS.pptxDSE-2, ANALYTICAL METHODS.pptx
DSE-2, ANALYTICAL METHODS.pptx
 
A Lecture on Sample Size and Statistical Inference for Health Researchers
A Lecture on Sample Size and Statistical Inference for Health ResearchersA Lecture on Sample Size and Statistical Inference for Health Researchers
A Lecture on Sample Size and Statistical Inference for Health Researchers
 
Estimating a Population Proportion
Estimating a Population Proportion  Estimating a Population Proportion
Estimating a Population Proportion
 

More from Kinshook Chaturvedi (20)

Working and functions_of_rbi[1]
Working and functions_of_rbi[1]Working and functions_of_rbi[1]
Working and functions_of_rbi[1]
 
Role of idfc_in_infrastucture_finance
Role of idfc_in_infrastucture_financeRole of idfc_in_infrastucture_finance
Role of idfc_in_infrastucture_finance
 
Mutual funds
Mutual fundsMutual funds
Mutual funds
 
Iifcl ppt
Iifcl pptIifcl ppt
Iifcl ppt
 
Basel ii norms.ppt
Basel ii norms.pptBasel ii norms.ppt
Basel ii norms.ppt
 
Retail banking pres
Retail banking presRetail banking pres
Retail banking pres
 
Presentation on lic of india
Presentation on lic of indiaPresentation on lic of india
Presentation on lic of india
 
Mfi dfi
Mfi dfiMfi dfi
Mfi dfi
 
Management of np as imt
Management of np as imtManagement of np as imt
Management of np as imt
 
Life insurance in india final raja
Life insurance in india final rajaLife insurance in india final raja
Life insurance in india final raja
 
Financial inclusion
Financial inclusionFinancial inclusion
Financial inclusion
 
Corporate banking v2
Corporate banking v2Corporate banking v2
Corporate banking v2
 
Corporate banking latest
Corporate banking latestCorporate banking latest
Corporate banking latest
 
Financial mgt exercises
Financial mgt exercisesFinancial mgt exercises
Financial mgt exercises
 
Csac10[1].p
Csac10[1].pCsac10[1].p
Csac10[1].p
 
Csac08[1].p
Csac08[1].pCsac08[1].p
Csac08[1].p
 
Csac05[1].p
Csac05[1].pCsac05[1].p
Csac05[1].p
 
Csac14[1].p
Csac14[1].pCsac14[1].p
Csac14[1].p
 
Csac06[1].p
Csac06[1].pCsac06[1].p
Csac06[1].p
 
Xyber001 16 12_09 (2)
Xyber001 16 12_09 (2)Xyber001 16 12_09 (2)
Xyber001 16 12_09 (2)
 

Recently uploaded

Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779Delhi Call girls
 
Dr. Admir Softic_ presentation_Green Club_ENG.pdf
Dr. Admir Softic_ presentation_Green Club_ENG.pdfDr. Admir Softic_ presentation_Green Club_ENG.pdf
Dr. Admir Softic_ presentation_Green Club_ENG.pdfAdmir Softic
 
HONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael HawkinsHONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael HawkinsMichael W. Hawkins
 
The Coffee Bean & Tea Leaf(CBTL), Business strategy case study
The Coffee Bean & Tea Leaf(CBTL), Business strategy case studyThe Coffee Bean & Tea Leaf(CBTL), Business strategy case study
The Coffee Bean & Tea Leaf(CBTL), Business strategy case studyEthan lee
 
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRLMONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRLSeo
 
Regression analysis: Simple Linear Regression Multiple Linear Regression
Regression analysis:  Simple Linear Regression Multiple Linear RegressionRegression analysis:  Simple Linear Regression Multiple Linear Regression
Regression analysis: Simple Linear Regression Multiple Linear RegressionRavindra Nath Shukla
 
A DAY IN THE LIFE OF A SALESMAN / WOMAN
A DAY IN THE LIFE OF A  SALESMAN / WOMANA DAY IN THE LIFE OF A  SALESMAN / WOMAN
A DAY IN THE LIFE OF A SALESMAN / WOMANIlamathiKannappan
 
Cracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptxCracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptxWorkforce Group
 
B.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptx
B.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptxB.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptx
B.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptxpriyanshujha201
 
VIP Call Girls In Saharaganj ( Lucknow ) 🔝 8923113531 🔝 Cash Payment (COD) 👒
VIP Call Girls In Saharaganj ( Lucknow  ) 🔝 8923113531 🔝  Cash Payment (COD) 👒VIP Call Girls In Saharaganj ( Lucknow  ) 🔝 8923113531 🔝  Cash Payment (COD) 👒
VIP Call Girls In Saharaganj ( Lucknow ) 🔝 8923113531 🔝 Cash Payment (COD) 👒anilsa9823
 
7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...Paul Menig
 
Famous Olympic Siblings from the 21st Century
Famous Olympic Siblings from the 21st CenturyFamous Olympic Siblings from the 21st Century
Famous Olympic Siblings from the 21st Centuryrwgiffor
 
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...Any kyc Account
 
How to Get Started in Social Media for Art League City
How to Get Started in Social Media for Art League CityHow to Get Started in Social Media for Art League City
How to Get Started in Social Media for Art League CityEric T. Tung
 
👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...
👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...
👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...rajveerescorts2022
 
John Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdfJohn Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdfAmzadHosen3
 

Recently uploaded (20)

Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
 
Dr. Admir Softic_ presentation_Green Club_ENG.pdf
Dr. Admir Softic_ presentation_Green Club_ENG.pdfDr. Admir Softic_ presentation_Green Club_ENG.pdf
Dr. Admir Softic_ presentation_Green Club_ENG.pdf
 
HONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael HawkinsHONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael Hawkins
 
The Coffee Bean & Tea Leaf(CBTL), Business strategy case study
The Coffee Bean & Tea Leaf(CBTL), Business strategy case studyThe Coffee Bean & Tea Leaf(CBTL), Business strategy case study
The Coffee Bean & Tea Leaf(CBTL), Business strategy case study
 
Forklift Operations: Safety through Cartoons
Forklift Operations: Safety through CartoonsForklift Operations: Safety through Cartoons
Forklift Operations: Safety through Cartoons
 
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
 
VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...
VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...
VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...
 
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRLMONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
 
Regression analysis: Simple Linear Regression Multiple Linear Regression
Regression analysis:  Simple Linear Regression Multiple Linear RegressionRegression analysis:  Simple Linear Regression Multiple Linear Regression
Regression analysis: Simple Linear Regression Multiple Linear Regression
 
A DAY IN THE LIFE OF A SALESMAN / WOMAN
A DAY IN THE LIFE OF A  SALESMAN / WOMANA DAY IN THE LIFE OF A  SALESMAN / WOMAN
A DAY IN THE LIFE OF A SALESMAN / WOMAN
 
unwanted pregnancy Kit [+918133066128] Abortion Pills IN Dubai UAE Abudhabi
unwanted pregnancy Kit [+918133066128] Abortion Pills IN Dubai UAE Abudhabiunwanted pregnancy Kit [+918133066128] Abortion Pills IN Dubai UAE Abudhabi
unwanted pregnancy Kit [+918133066128] Abortion Pills IN Dubai UAE Abudhabi
 
Cracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptxCracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptx
 
B.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptx
B.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptxB.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptx
B.COM Unit – 4 ( CORPORATE SOCIAL RESPONSIBILITY ( CSR ).pptx
 
VIP Call Girls In Saharaganj ( Lucknow ) 🔝 8923113531 🔝 Cash Payment (COD) 👒
VIP Call Girls In Saharaganj ( Lucknow  ) 🔝 8923113531 🔝  Cash Payment (COD) 👒VIP Call Girls In Saharaganj ( Lucknow  ) 🔝 8923113531 🔝  Cash Payment (COD) 👒
VIP Call Girls In Saharaganj ( Lucknow ) 🔝 8923113531 🔝 Cash Payment (COD) 👒
 
7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...
 
Famous Olympic Siblings from the 21st Century
Famous Olympic Siblings from the 21st CenturyFamous Olympic Siblings from the 21st Century
Famous Olympic Siblings from the 21st Century
 
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
 
How to Get Started in Social Media for Art League City
How to Get Started in Social Media for Art League CityHow to Get Started in Social Media for Art League City
How to Get Started in Social Media for Art League City
 
👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...
👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...
👉Chandigarh Call Girls 👉9878799926👉Just Call👉Chandigarh Call Girl In Chandiga...
 
John Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdfJohn Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdf
 

Freq distribution

  • 1. Frequency Distribution, Cross-Tabulation, and Hypothesis Testing
  • 2.
  • 3.
  • 4.
  • 5.
  • 6. Internet Usage Data Respondent Sex Familiarity Internet Attitude Toward Usage of Internet Number Usage Internet Technology Shopping Banking 1 1.00 7.00 14.00 7.00 6.00 1.00 1.00 2 2.00 2.00 2.00 3.00 3.00 2.00 2.00 3 2.00 3.00 3.00 4.00 3.00 1.00 2.00 4 2.00 3.00 3.00 7.00 5.00 1.00 2.00 5 1.00 7.00 13.00 7.00 7.00 1.00 1.00 6 2.00 4.00 6.00 5.00 4.00 1.00 2.00 7 2.00 2.00 2.00 4.00 5.00 2.00 2.00 8 2.00 3.00 6.00 5.00 4.00 2.00 2.00 9 2.00 3.00 6.00 6.00 4.00 1.00 2.00 10 1.00 9.00 15.00 7.00 6.00 1.00 2.00 11 2.00 4.00 3.00 4.00 3.00 2.00 2.00 12 2.00 5.00 4.00 6.00 4.00 2.00 2.00 13 1.00 6.00 9.00 6.00 5.00 2.00 1.00 14 1.00 6.00 8.00 3.00 2.00 2.00 2.00 15 1.00 6.00 5.00 5.00 4.00 1.00 2.00 16 2.00 4.00 3.00 4.00 3.00 2.00 2.00 17 1.00 6.00 9.00 5.00 3.00 1.00 1.00 18 1.00 4.00 4.00 5.00 4.00 1.00 2.00 19 1.00 7.00 14.00 6.00 6.00 1.00 1.00 20 2.00 6.00 6.00 6.00 4.00 2.00 2.00 21 1.00 6.00 9.00 4.00 2.00 2.00 2.00 22 1.00 5.00 5.00 5.00 4.00 2.00 1.00 23 2.00 3.00 2.00 4.00 2.00 2.00 2.00 24 1.00 7.00 15.00 6.00 6.00 1.00 1.00 25 2.00 6.00 6.00 5.00 3.00 1.00 2.00 26 1.00 6.00 13.00 6.00 6.00 1.00 1.00 27 2.00 5.00 4.00 5.00 5.00 1.00 1.00 28 2.00 4.00 2.00 3.00 2.00 2.00 2.00 29 1.00 4.00 4.00 5.00 3.00 1.00 2.00 30 1.00 3.00 3.00 7.00 5.00 1.00 2.00 Table 15.1
  • 7.
  • 8. Frequency Distribution of Familiarity with the Internet Table 15.2
  • 9. Frequency Histogram Figure 15.1 2 3 4 5 6 7 0 7 4 3 2 1 6 5 Frequency Familiarity 8
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16. Skewness of a Distribution Figure 15.2 Skewed Distribution Symmetric Distribution Mean Median Mode (a) Mean Median Mode (b)
  • 17. Steps Involved in Hypothesis Testing Fig. 15.3 Draw Marketing Research Conclusion Formulate H 0 and H 1 Select Appropriate Test Choose Level of Significance Determine Probability Associated with Test Statistic Determine Critical Value of Test Statistic TSCR Determine if TSCR falls into (Non) Rejection Region Compare with Level of Significance,  Reject or Do not Reject H 0 Collect Data and Calculate Test Statistic
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24. Probabilities of Type I & Type II Error Figure 15.4 99% of Total Area Critical Value of Z   = 0.40  = 0.45  = 0.01 = 1.645 Z  = -2.33 Z  Z Z 95% of Total Area  = 0.05
  • 25. Probability of z with a One-Tailed Test Unshaded Area = 0.0301 Fig. 15.5 Shaded Area = 0.9699 z = 1.88 0
  • 26.
  • 27. A General Procedure for Hypothesis Testing Step 4: Collect Data and Calculate Test Statistic The test statistic z can be calculated as follows: = 0.567-0.40 0.089 = 1.88 In Words: “Our sample value was 1.88 Standard Deviations above our Hypothesized Mean Value How likely is it that actual population value is <.4? Our “hypothesized” population value (>.4) Our Sample Value or Estimate: 17/30 Std Error Estimate 3.1% 2.5%
  • 28.
  • 29.
  • 30.
  • 31.
  • 32. A Broad Classification of Hypothesis Tests Figure 15.6 Median/ Rankings Distributions Means Proportions Tests of Association Tests of Differences Hypothesis Tests
  • 33.
  • 34. Gender and Internet Usage Table 15.3
  • 35.
  • 36. Internet Usage by Gender Table 15.4
  • 37. Gender by Internet Usage Table 15.5
  • 40. CROSSTAB RESULTS Appears to be relationship between Gender and Internet Usage: Is it Significant ?
  • 41. CROSSTAB SIGNIFICANCE There is NO statistical relationship between gender and internet usage at 5% Level! Must be >3.841 To Accept Alternative Hypothesis
  • 42. Introduction of a Third Variable in Cross-Tabulation Fig. 15.7 Refined Association between the Two Variables No Association between the Two Variables No Change in the Initial Pattern Some Association between the Two Variables Some Association between the Two Variables No Association between the Two Variables Introduce a Third Variable Introduce a Third Variable Original Two Variables
  • 43.
  • 44. Purchase of Fashion Clothing by Marital Status Table 15.6
  • 45. Purchase of Fashion Clothing by Marital Status Table 15.7
  • 46.
  • 47. Ownership of Expensive Automobiles by Education Level Table 15.8
  • 48. Ownership of Expensive Automobiles by Education Level and Income Levels Table 15.9
  • 49.
  • 50. Desire to Travel Abroad by Age Table 15.10
  • 51. Desire to Travel Abroad by Age and Gender Table 15.11
  • 52.
  • 53. Eating Frequently in Fast-Food Restaurants by Family Size Table 15.12
  • 54. Eating Frequently in Fast Food-Restaurants by Family Size & Income Table 15.13
  • 55.
  • 56. Chi-square Distribution Figure 15.8 Reject H 0 Do Not Reject H 0 Critical Value  2
  • 57.
  • 58.
  • 59.
  • 60.
  • 61.
  • 62.
  • 63.
  • 64.
  • 65.
  • 66.
  • 67.
  • 68.
  • 69.
  • 70.
  • 71.
  • 72.
  • 73. One Sample t Test 4.724 5.017 5.310 2.75% Probability
  • 74.
  • 75.
  • 76.
  • 77.
  • 78.
  • 79.
  • 80.
  • 81.
  • 82.
  • 83.
  • 84. Two Independent-Samples t Tests Table 15.14 -
  • 85.
  • 86.
  • 87.
  • 88.
  • 89.
  • 90.
  • 91. Paired-Samples t Test Number Standard Standard Variable of Cases Mean Deviation Error Internet Attitude 30 5.167 1.234 0.225 Technology Attitude 30 4.100 1.398 0.255 Difference = Internet - Technology Difference Standard Standard 2 - tail t Degrees of 2 - tail Mean deviat ion error Correlation prob. value freedom probability 1.067 0.828 0 .1511 0 .809 0 .000 7.059 29 0 .000 Table 15.15
  • 92.
  • 93.
  • 94.
  • 95. K-S One-Sample Test for Normality of Internet Usage Table 15.16
  • 96.
  • 97.
  • 98.
  • 99. Mann-Whitney U - Wilcoxon Rank Sum W Test Internet Usage by Gender Table 15.17 Sex Mean Rank Cases Male 20.93 15 Female 10.07 15 Total 30 Corrected for ties U W z 2 - tailed p 31.000 151.000 - 3.406 0.001 Note U = Mann - Whitney test statistic W = Wilcoxon W Statistic z = U transformed into a normally distributed z stat istic.
  • 100.
  • 101.
  • 102. Wilcoxon Matched-Pairs Signed-Rank Test Internet with Technology Table 15.18
  • 103. A Summary of Hypothesis Tests Related to Differences Table 15.19 Contd.
  • 104. A Summary of Hypothesis Tests Related to Differences Table 15.19 cont.
  • 105.
  • 106.
  • 107.
  • 108.