Analysis Variables

Question: Give a Descriptive Analysis for the variables. Answer: It is observed that out of 196 respondents, about 121 respondents used the mobile for checking the instagram page while the 48 users use the computer for checking the instagram page. About 27 users or respondents use the tablet for checking the new launched instagram page. It is observed that the about 70 users use the morning time for accessing the instagram page while 31 respondents use the midday time for the same purpose. It is observed that about 44 users or respondents use the afternoon time for checking instagram page while about 51 respondents use the night time for accessing the instagram page. It is observed that there are 91 male respondent and 105 female respondents present in the given data set. The average length of time for the male is observed as the 42.63 seconds with the standard deviation of 21.67 seconds while the average length of time for the female is observed as 46 seconds with the standard deviation of 24.25 seconds. The average perception of instagram is giv en as 25.1786 with the standard deviation of 17.94. The correlation coefficient is found as 0.073 which means there is a very weak linear association or correlation or linear relationship exists between the given two variables gender and length of time. The multiple regression coefficients between the dependent variable number of times visited and independent variables length of time and perception of instagram is given as 0.726 which means there is a considerable amount of relationship exists between the given dependent and independent variables. The coefficient of determination or the value of the R square is given as 0.527 which means about 52.7% of the variation in the dependent variable is explained by the independent variables such as length of time and perception of instagram. Descriptive Analysis In this section we have to see the descriptive statistics for the variables included in the given data set. As we know that the descriptive statistics gives us the general idea about the variable under study. Descriptive statistics consist of the study of the mean, mode, median, maximum, minimum, standard deviation, range, etc. Let us see this descriptive statistics for the different variables under study given as below: First of all we have to see the frequency distribution for the device used for the purpose of checking the instagram page. The frequency distribution is given as below: 18271645_1 = MOBILE, 2 = TABLET, 3 = COMPUTER Frequency Percent Valid Percent Cumulative Percent Valid Mobile 121 61.7 61.7 61.7 Tablet 27 13.8 13.8 75.5 Computer 48 24.5 24.5 100.0 Total 196 100.0 100.0 From this table it is observed that out of 196 respondents, about 121 respondents used the mobile for checking the instagram page while the 48 users use the computer for checking the instagram page. About 27 users or respondents use the tablet for checking the new launched instagram page. Now, we have to see the bar chart for the above frequency distribution for the type of device used for checking the instagram page. The bar chart is given as below: Now, we have to see the frequency distribution for the time of the day used by the user for checking or accessing the instagram page. The frequency distribution for the time of the day used by the user for accessing the instagram page is given as below: 18271645_1 = MORNING, 2 = MIDDAY, 3 = AFTERNOON, 4 = NIGHT Frequency Percent Valid Percent Cumulative Percent Valid Morning 70 35.7 35.7 35.7 Midday 31 15.8 15.8 51.5 Afternoon 44 22.4 22.4 74.0 Night 51 26.0 26.0 100.0 Total 196 100.0 100.0 From this frequency distribution it is observed that the about 70 users use the morning time for accessing the instagram page while 31 respondents use the midday time for the same purpose. It is observed that about 44 users or respondents use the afternoon time for checking instagram page while about 51 respondents use the night time for accessing the instagram page. Now, we have to see the bar diagram for the above frequency distribution for the time of the day used by the user for accessing the instagram page which is given as below: From this bar diagram it is observed that most of the users use the instagram page at the morning time. So, it is recommended that focus on the morning time for making more advertisements or other activities when most of the users are online. Now, we have to see the frequency distribution for the gender of the respondent which is given as below: 18271645_1 = FEMALE, 2 = MALE Frequency Percent Valid Percent Cumulative Percent Valid Male 91 46.4 46.4 46.4 Female 105 53.6 53.6 100.0 Total 196 100.0 100.0 From the above table, it is observed that there are 91 male respondent and 105 female respondents present in the given data set. The bar diagram for this frequency distribution is given as below: For the variable length of time in seconds, the descriptive statistics for the male and female are summarised in the following table: Group Statistics 18271645_1 = FEMALE, 2 = MALE N Mean Std. Deviation Std. Error Mean 18271645_LENGTH OF TIME (SECONDS) Male 91 42.6264 21.66649 2.27126 Female 105 46.0000 24.24554 2.36612 The average length of time for the male is observed as the 42.63 seconds with the standard deviation of 21.67 seconds while the average length of time for the female is observed as 46 seconds with the standard deviation of 24.25 seconds. Now, we have to see the descriptive statistics for the variable perception of instagram which is summarised in the following table: Descriptive Statistics N Minimum Maximum Mean Std. Deviation 18271645_PERCEPTION OF INSTAGRAM (Constant sum) 196 .00 60.00 25.1786 17.94018 Valid N (listwise) 196 The average perception of instagram is given as 25.1786 with the standard deviation of 17.94. Now, we have to see the variation pattern for the four items of social posers instagram involvements. The standard deviations for these variables are summarised as below: Descriptive Statistics N Std. Deviation 18271645_II_5: Instagram is great for sharing my life with others 196 1.82732 18271645_II_7: I could go a week without visiting Instagram 196 1.84209 18271645_II_8: All my friends use Instagram regularly 196 1.93486 18271645_II_10: I care about what people think of my Instagram account 196 1.86167 Valid N (listwise) 196 Inferential Analysis In this section, first of all we have to see the correlation coefficients between the two variables gender and length of the time which is given as below: Correlations 18271645_1 = FEMALE, 2 = MALE 18271645_LENGTH OF TIME (SECONDS) 18271645_1 = FEMALE, 2 = MALE Pearson Correlation 1 .073 Sig. (2-tailed) .309 N 196 196 18271645_LENGTH OF TIME (SECONDS) Pearson Correlation .073 1 Sig. (2-tailed) .309 N 196 196 The correlation coefficient is found as 0.073 which means there is a very weak linear association or correlation or linear relationship exists between the given two variables. Now, we have to see the regression model for the purpose of the prediction of the dependent variable number of times repeated. The regression model is given as below: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .726a .527 .522 2.17910 a. Predictors: (Constant), 18271645_LENGTH OF TIME (SECONDS), 18271645_PERCEPTION OF INSTAGRAM (Constant sum) The multiple regression coefficient between the dependent variable number of times visited and independent variables length of time and perception of instagram is given as 0.726 which means there is a considerable amount of relationship exists between the given dependent and independent variables. The coefficient of determination or the value of the R square is given as 0.527 which means about 52.7% of the variation in the dependent variable is explained by the independent variables such as length of time and perception of instagram. The ANOVA table for this regression analysis is given as below: ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1019.848 2 509.924 107.387 .000a Residual 916.453 193 4.748 Total 1936.301 195 a. Predictors: (Constant), 18271645_LENGTH OF TIME (SECONDS), 18271645_PERCEPTION OF INSTAGRAM (Constant sum) b. Dependent Variable: 18271645_FIRST MONTH OF LAUNCH (number of times visited) For this regression analysis we get the p-value as 0.00 which is less than the given level of significance or alpha value 0.05, so we reject the null hypothesis that the given regression model is significant. This means the regression model is not significant. The coefficients for this regression model are summarised in the following table: Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .307 .352 .872 .384 18271645_PERCEPTION OF INSTAGRAM (Constant sum) .113 .010 .641 11.655 .000 18271645_LENGTH OF TIME (SECONDS) .022 .008 .161 2.921 .004 a. Dependent Variable: 18271645_FIRST MONTH OF LAUNCH (number of times visited) The regression equation for the above regression analysis is given as below: Number of times visited = 0.307 + 0.113*Perception of instagram + 0.022*length of time Results and Interpretations It is observed that out of 196 respondents, about 121 respondents used the mobile for checking the instagram page while the 48 users use the computer for checking the instagram page. About 27 users or respondents use the tablet for checking the new launched instagram page. It is observed that the about 70 users use the morning time for accessing the instagram page while 31 respondents use the midday time for the same purpose. It is observed that about 44 users or respondents use the afternoon time for checking instagram page while about 51 respondents use the night time for accessing the instagram page. It is observed that there are 91 male respondent and 105 female respondents present in the given data set. The average length of time for the male is observed as the 42.63 seconds with the standard deviation of 21.67 seconds while the average length of time for the female is observed as 46 seconds with the standard deviation of 24.25 seconds. The average perception of instagram is given as 25.1786 with the standard deviation of 17.94. The correlation coefficient is found as 0.073 which means there is a very weak linear association or correlation or linear relationship exists between the given two variables gender and length of time. References Schervish, Mark J. (1995). Theory of statistics (Corr. 2nd print. ed.). New York: Springer Moses, Lincoln E. (1986) Think and Explain with Statistics, Addison-Wesley Hays, William Lee, (1973) Statistics for the Social Sciences, Holt, Rinehart and Winston Rubin, Donald B.; Little, Roderick J. A., Statistical analysis with missing data, New York: Wiley 2002 Mosteller, F., Tukey, J. W. (1977). Data analysis and regression. Boston: Addison-Wesley. Mann, Prem S. (1995). Introductory Statistics (2nd ed.). Wiley. Babbie, Earl R. (2009). The Practice of Social Research (12th ed.). Wadsworth. Nick, Todd G. (2007). "Descriptive Statistics". Topics in Biostatistics.New York: Springer. Trochim, William M. K. (2006). "Descriptive statistics". Research Methods Knowledge Base.