Summary of Quantitative Effects:
Question one particular includes a result of a regression analysis. Benefits have unveiled whether there is a relationship between ‘age' and ‘shopping in-store'. From ANOVAb, it implies that sig. (0. 024), which can be less than 0. 05, which means there is a romantic relationship between era and in-store shopping. In line with the ‘Model Summary' table, L equals to zero. 357, meaning there is a somewhat positive romantic relationship and grow older can be 12. 7% connect to in-store buying (R Sq = 0. 127); basically, people who is older would choose shopping in-store. For the relationship between ‘age' and ‘choose of on the web shopping' By ANOVAb, because sig. (0. 024) is less than 0. 05, it means there exists a relationship between age and online shopping, in line with the ‘Model Summary' table, 3rd there�s r equals to -0. 357, this means that there is a rather negative marriage and age group can be doze. 7% url to online shopping (R Square sama dengan 0. 127); in other words, people that is elderly do not want to shop online.
Question a couple of presents the consequence of one-way ANOVA. Results uncovered the relationship among ‘educational level' and ‘choose of in-store shopping', through the use of ANOVA evaluation, it is clear that it is certainly not statistically factor among distinct educational level; in other words, different education level would not substantially affect peoples' choice of in-store shopping (Sig = 0. 515 > 0. 05). All results are the same among ‘educational level' and ‘choose of on the web shopping' in other words, different education level may not significantly have an effect on people's choice of shopping online (Sig = 0. 515 > 0. 05).
Problem 3 statement the result of the regression examination. Results exposed the fact there is no romance between ‘income level' and ‘choose of in-store shopping'. From ANOVAb, as sig. (0. 228) is more than 0. 05, there is no relationship between cash flow level and in-store shopping. All results are the same among ‘income level' and ‘choose of on the net shopping' There is not any relationship between these two parameters.
Question 5 presents an index of one-way ANOVA on ‘age groups' and ‘product acquired in-store'. By using the ANOVA test out, it is clear that there is simply no statistically significant difference among several age groups; in other words, different age ranges would not drastically affect persons purchase what kinds of products in-store (Sig sama dengan 0. 428 > zero. 05). On the other hand, ANOVA evaluation is being used to revealed if there is a romance between ‘age groups' and ‘product acquired online' and it is clear you cannot find any statistically factor among diverse age groups; put simply, different age ranges would not considerably affect the type of product people order online (Sig = zero. 169 > 0. 05).
Question 5 reports a statistical synopsis of a Chi-Square test. Benefits revealed the partnership between ‘marital stage' and ‘products obtain in-store', through the use of Chi-Square test out, it is clear that there is statistically significant difference among different relationship stage; put simply, different significant other stage might significantly have an effect on what products do people purchase in-store (Sig = 0. 500 < zero. 05). Chi-Square test is used in order to investigate the relationship between ‘marital status' plus the ‘products that individuals purchase in-store. The result shows the fact that no statistically significant was found among different relationship stage; in other words, different significant other stage may not significantly have an effect on people's selection of products that they purchase on the web (Sig sama dengan 0. 428 > 0. 05).
Problem 6 reviews the result of a Chi-Square test out. Results have got revealed the relationship between ‘gender' and ‘products purchase in-store'. By using Chi-Square test, it really is clear there is a statistically significant difference between male and feminine. In other words, the types of products that are being purchased in-store is different when comparing male to female (Sig = zero. 031 < 0. 05). For example , man...