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Gender Differences in Monthly Lunch or Dinner Spending - Case Study Example

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The paper "Gender Differences in Monthly Lunch or Dinner Spending" states that Levene's Test for Equality of Variances was statistically significant for average monthly expenditure. Therefore, the null hypothesis is rejected in favour of the alternative hypothesis…
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Gender Differences in Monthly Lunch or Dinner Spending
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?SPSS APA, 10 pages Question Descriptive Analysis Table shows the various variables, their question numbers, correct measures and the descriptivestatistics which are appropriate for each of the variables. Variable # Name Question # Measure Central Tendency Value Dispersion Value 1 Totspent 2 Scale(Ratio) Mean 158.59 SD 90.78 2 Watchtv 3 Nominal Mode 1 - 3 Tvprogram 4 Nominal Mode 3 - 4 Tvnewsviewer 5 Nominal Mode 1 - 5 Newstime 6 Nominal Mode 4 - 6 Surfnet 7 Nominal Mode 3 - 7 Websitevisit 8 Nominal Mode 3 - 8 Smartphone 9 Nominal Mode 2 - 9 Location 10 Ordinal Median 2 Percentile 1.50; 4.00 10 Distance 10 Ordinal Median 4 Percentile 2; 4 11 Wine 10 Ordinal Median 4 Percentile 2; 5 12 Chef 10 Ordinal Median 4 Percentile 2; 5 13 Waitstaff 10 Ordinal Median 4 Percentile 2; 5 14 Unique 10 Ordinal Median 4 Percentile 2; 5 15 Local 10 Ordinal Median 2 Percentile 1; 4 16 Attractive 10 Ordinal Median 4 Percentile 2; 5 17 Music 10 Ordinal Median 4 Percentile 2; 5 18 Parking 10 Ordinal Median 2 Percentile 1; 3 19 Likely 11 Scale(Ratio) Mean 3 SD 1.23 20 Avprice 12 Scale(Ratio) Mean 24.10 SD 10.11 21 Birthyear 13 Scale(Ratio) Mean SD 21 Age 13 Scale(Ratio) Mean 45.48 SD 9.99 22 Education 14 Ordinal Median 6 Percentile 6; 6 23 Maritalstatus 15 Nominal Mode 2 - 24 Hometype 16 Nominal Mode 4 - 25 Familysize 17 Scale(Ratio) Mean 2.64 SD 1.38 26 Zipcode 18 Nomimal Mode 3 - 27 Income 19 Ordinal Median 4 Percentile 3; 6 28 Gender 20 Nominal Mode 1 - Table 2 shows the variables whose measures were changed as there were coding errors in them. The variable name is shown together with the question number, the correct measure and the change that was made. The reason for the change is also provided. Name Question # Measure Changes Reason for change Tvprogram 4 Nominal Changed from ‘scale’ to ‘nominal’ Coding error Surfnet 7 Nominal Changed from ‘scale’ to ‘nominal’ Coding error Location 10 Ordinal Changed from ‘scale’ to ‘ordinal’ Coding error Distance 10 Ordinal Changed from ‘scale’ to ‘ordinal’ Coding error Wine 10 Ordinal Changed from ‘nominal’ to ‘ordinal’ Coding error Chef 10 Ordinal Changed from ‘scale’ to ‘ordinal’ Coding error Waitstaff 10 Ordinal Changed from ‘scale’ to ‘ordinal’ Coding error Unique 10 Ordinal Changed from ‘nominal’ to ‘ordinal’ Coding error Local 10 Ordinal Changed from ‘nominal’ to ‘ordinal’ Coding error Attractive 10 Ordinal Changed from ‘scale’ to ‘ordinal’ Coding error Music 10 Ordinal Changed from ‘scale’ to ‘ordinal’ Coding error Parking 10 Ordinal Changed from ‘nominal’ to ‘ordinal’ Coding error Birthyear 13 Scale (Ratio) Changed from ‘nominal’ to ‘scale’ Coding error Income 19 Ordinal Changed from ‘nominal’ to ‘ordinal’ Coding error Question 2 Gender Differences in Monthly Lunch or Dinner Spending This study examines whether male and female differ in their monthly spending on lunch or dinner at restaurants. In order to achieve this, the following hypothesis was tested using Independent-Samples T-Test: H0: There are no significant differences by gender in monthly expenditures on lunch or dinner at restaurants. H1: There are significant differences by gender in monthly expenditures on lunch or dinner at restaurants The results show that female (M = $ 169.99, SD = $ 86.79) spent more than male (M = $ 148.34, SD = $ 93.27) on lunch or dinner at restaurants monthly. The Levene’s Test for Equality of Variances was statistically significant for average monthly expenditure (p < .05). Therefore, the null hypothesis is rejected in favour of alternative hypothesis. These results support the claim by Chef Gatson that men and women are different in terms of the amount they spend, on a monthly basis, on lunch or dinner at restaurant. Therefore, female spend more than male on lunch and dinner in restaurants on a monthly basis. The study recommends that Chef Gaston should focus on having lunch and dinner packages that will attract more female clients to the restaurant. Since they spend more than male clients on a monthly basis on lunch and dinner, the sales revenues are likely to improve if more female clients can be attracted to the new restaurant. Gender Differences in Expected Average Price for Evening Entree Items The study also examined whether there were gender differences in expected average price for evening entree items alone. Thus, the following hypothesis was tested using Independent-Samples T-Test: H0: There are no significant differences by gender in expected average price for evening entree item alone. H1: There are significant differences by gender in expected average price for evening entree item alone. The results show that males expected the average price for evening entree item alone to be higher (M = $ 24.51, SD = $ 10.46) than did the female (M = $ 23.63, SD = $ 9.72). These differences are statistically insignificant (p > .05). The null hypothesis is therefore accepted. These results do not support the chef’s claims that they male and female differ in terms of their expected average price for evening entree item alone. From these results, it is recommended that a pricing strategy will not affect the number of males or females who will come to the restaurant if the evening entree item can be served between $ 24.51 and $ 23.63. Both male and female patronisers’ average pricing was not significantly varied and therefore would not affect the sales in the restaurant. Differences in Preference for Attractive Decor by Status of TV Watching The study further examined whether there were differences between those who watched television and those who did not in terms of the level of importance attached to attractive decor. The following hypothesis was tested using Independent-Samples T-Test: H0: There are no significant differences in the importance attached to attractive decor between people who watch television and those who don’t. H1: There are significant differences in the importance attached to attractive decor between people who watch television and those who don’t. The results show that those who did not watch TV (M = 4.27, SD = 1.39) considered attractive decor more important than those who watched TV (M = 3.65, SD = 1.52). The test of significance shows that the differences were statistically insignificant (p > .05). Thus, the null hypothesis was accepted. The results do not support Chef Gaston’s claims that people who watch TV and those who don’t differ in the levels of importance attached to attractive decor. Chef Gaston therefore should market the restaurant to both groups irrespective of whether they watch TV or not. H0: There are significant differences in the importance attached to valet parking between people who watch television and those who don’t. H1: There are no significant differences in the importance attached to valet parking between people who watch television and those who don’t. The results show that those who watch TV (M = 2.30, SD = 1.21) considered free valet parking more important than those who did not watch TV (M = 2.20, SD = 1.57). The test of significance shows that the differences were statistically insignificant (p > .05). Therefore, the null hypothesis was accepted. The results do not support Chef Gaston’s claims that people who watch TV and those who don’t differ in the levels of importance attached to valet parking. The study recommends that Chef Gaston should not worry about differences in importance attached to valet parking on the basis of whether one watched TV or not as they did attach the same level of importance. Question 3 Effect of Education on Likelihood to Patronize the Restaurant H0: The level of education does not affect the likelihood of customers patronizing the restaurant H1: The level of education affects the likelihood of customers patronizing the restaurant The descriptive results of the one-way ANOVA test show that the likelihood to dine at the restaurant rises as the levels of education rise from less than High School (M = 1.40, SD = .699) to doctorate degree (M = 4.75, SD = .707). The ANOVA results show that these differences were statistically significant (F [7, 28.48] = 29.61, p < .01). These results lead to the rejection of null hypothesis and acceptance of the alternate hypothesis. Thus, Chef Gaston is correct in his assumption that customers with more education are more likely to patronize the new restaurant. These results lead to the conclusion that it is important for Chef Gaston’s restaurant to market itself to those with higher levels of education, especially those with at least a Bachelor’s degree (who make up 84% of those who are likely to patronize at the restaurant). Serving this market will see the sales rise from the launch of the restaurant. Question 4 Important Restaurant Characteristics of Potential Patrons The study examined the factors that were considered important by potential patrons in terms of wine selection, famous chef, locally-sourced ingredients, and live music. A one-sample t-test was run on the following hypotheses after selecting cases: H0a: Potential clients who are completely likely to patronize the restaurant will not consider wine selection as completely important. H1a: Potential clients who are completely likely to patronize the restaurant will consider wine selection as completely important. The results show that that clients who are completely likely to patronise the restaurant will consider wine selection as completely important (M = 1.33, SD = .475, p < .01). The null hypothesis is rejected because the p-value is less than 1%. It is recommended that Chef Gaston should understand that those who are certain of being clients in the restaurant will consider wine selection very important and therefore wine selection should be at the core of the marketing campaign for the new restaurant as it appeals to the potential clients who are certain of patronising the restaurant. H0b: Potential clients who are completely likely to patronize the restaurant will not consider famous chef as completely important. H1b: Potential clients who are completely likely to patronize the restaurant will consider famous chef as completely important. The results show that that clients who are completely likely to patronise the restaurant will consider famous chef as completely important (M = 1.46, SD = .502, p < .01). The null hypothesis is rejected because the p-value is less than 1%. It is recommended that Chef Gaston should be cognizant of the fact that those who are certain of being clients in the restaurant will consider famous chef very important and therefore famous chef should be at the center of the marketing campaign for the new restaurant as it appeals to the potential clients who are certain of patronising the restaurant. H0c: Potential clients who are completely likely to patronize the restaurant will not consider locally-sourced ingredients as completely important. H1c: Potential clients who are completely likely to patronize the restaurant will consider locally-sourced ingredients as completely important. The results show that that clients who are completely likely to patronise the restaurant will consider locally-sourced ingredients as completely important (M = 4.52, SD = .503, p < .01). The null hypothesis is rejected because the p-value is less than 1%. It is recommended that Chef Gaston should understand that those who are certain of being clients in the restaurant will consider use of locally-sourced ingredients very important and therefore locally-sourced ingredients should be at the core of the marketing campaign for the new restaurant as it appeals to the potential clients who are certain of patronising the restaurant. H0d: Potential clients who are completely likely to patronize the restaurant will not consider live music as completely important. H1d: Potential clients who are completely likely to patronize the restaurant will consider live music as completely important. The results show that that clients who are completely likely to patronise the restaurant will consider live music as completely important (M = 1.63, SD = .485, p < .01). The null hypothesis is rejected because the p-value is less than 1%. It is recommended that Chef Gaston should understand that those who are certain of being clients in the restaurant will consider live music very important and therefore live music should be at the core of the marketing campaign for the new restaurant as it appeals to the potential clients who are certain of patronising the restaurant. Question 5 The Influence of Household Income on Likelihood to Patronize the Restaurant The study sought to determine whether the household income influenced the likelihood of customers to patronize the restaurant. A t-test was undertaken to test the following hypothesis. H0: Customers with higher household income are not likely to patronize at the restaurant H1: Customers with higher household income are likely to patronize at the restaurant The descriptive results show that the number of customer who are likely to patronise the restaurant rises with the income levels from lowest income (M = 1.26, SD = .619) to the highest income (M = 4.32, SD = .901). The ANOVA results show that these differences are statistically significant (F [6, 356] = 157.16, p < .01, ?2 = .729). The null hypothesis is therefore rejected in favour of the alternate hypothesis. The results lead to the conclusion that household income influences the likelihood to patronise at the restaurant. People with higher incomes are more likely to patronise at the restaurant than those with low incomes. Therefore, Chef Gaston should target those with higher incomes as they are likely to patronize at the restaurant. The Influence of Television Program on Likelihood to Patronize the Restaurant The study sought to determine whether the type of television program influenced the likelihood of customers to patronize the restaurant. A t-test was used to test the following hypothesis. H0: Type of television program does not influence the likelihood of customers to patronize the restaurant H1: Type of television program influences the likelihood of customers to patronize the restaurant The results show that the customers likelihood to patronise the restaurant differs by the type of television program watched, F (3, 341) = 113.82, p < .01. Therefore, the null hypothesis is rejected as the p value is less than 1%. From these results, Chef Gaston should be encouraged to focus his branding and marketing to those who watch comedy (could be families with children) for their lunch and dinner menus. Further, the restaurant should also focus on those who like watching talk shows. These could be women or families or both. Question 6 Appeal for Restaurant The study sought to assess differences in appeal for Chef Gaston’s Restaurant by gender, type of program watched on television, hours spent surfing the internet, and type of website surfed most. In order to carry out this analysis, independent-sample T-tests were performed on the following hypotheses: H0a: Appeal for the restaurant does not differ by gender. H1a: Appeal for the restaurant differs by gender. The results show that the appeal for the restaurant does not differ between men and women, F (1, 211) = 2.65, p > .105. The null hypothesis is accepted. The appeal for the restaurant does not differ for men and women. Therefore, it would be appropriate that Chef Gaston’s restaurant be marketed to both men and women as they did not differ in their appeal for this kind of restaurant. H0b: Appeal for restaurant does not differ by type of program watched on television. H1b: Appeal for restaurant differs by type of program watched on television. The results show that the appeal was higher differed between the type of program watched on television, F (3, 211) = 58.97, p < .01. The null hypothesis is therefore rejected in favour of the alternate hypothesis. This means that there was difference in appeal for the restaurant by the type of program watched most on television. The restaurant should therefore be marketed to a specific kind of clients who mostly watch comedy and talk shows more than those watch sports. H0c: Appeal for restaurant does not differ by number of hours spent surfing on the Internet. H1c: Appeal for restaurant differs by number of hours spent surfing on the Internet. The results reveal that the appeal differed by number of hours spent surfing the internet, F (5, 211) = 7.34, p < .01. The null hypothesis of no difference is therefore rejected. Therefore, Chef Gaston needs to devote most of his time and resources marketing the restaurant on the Internet to internet savvy individuals as his target market is significantly influenced by the time spent on the Internet a day. H0d: Appeal for restaurant does not differ by type of website individuals spent most time on. H1d: Appeal for restaurant does not differ by type of website individuals spent most time on. The results show that the appeal for the restaurant differs by the type of website, F (4, 211) = 8.36, p .05. We therefore accept the null hypothesis as the p value is more than 1%. Chef Gaston should not therefore focus on only one aspect as both were important. H0: There are no differences between unique menu and sourcing of local ingredients in influencing the likelihood to patronize the restaurant. H1: There are no differences between unique menu and sourcing of local ingredients in influencing the likelihood to patronize the restaurant. The results showed that unique menu (M = 3.60, SD = 1.54) had higher influence on likelihood to patronise than locally-sourced ingredients (M = 2.43, SD = 1.48). The differences were significant, p < .01. We therefore reject the null hypothesis as the p value is less than 1%. Chef Gaston should therefore focus on having a unique menu than on sourcing local ingredients. H0: There are no differences between better wine selection and free valet parking in influencing the likelihood to patronize the restaurant. H1: There are no differences between better wine selection and free valet parking in influencing the likelihood to patronize the restaurant. The results showed that wine selection (M = 3.54, SD = 1.50) had higher influence on likelihood to patronise than free valet parking (M = 2.30, SD = 1.22). The differences were significant, p < .01. We therefore reject the null hypothesis as the p value is less than 1%. Chef Gaston should therefore focus on having better wine selection than on free parking. Question 8 Customer Targeting The study examined a number of issues on the customers using H0: The average monthly spending on meals only is not significantly different from $ 150. H1: The average monthly spending on meals only is significantly different from $ 150. A one sample t-test was conducted on age to evaluate whether the spending mean was significantly different from $150, the accepted mean for customers monthly spending. The sample mean of $158.59 (SD = 90.78) was not significantly different from $150, t (356) = 1.79, p > .07. The results lead to the acceptance of null hypothesis since the p value is more than 5%. The restaurant can therefore price the meals at $150 if that price is right for the meals only as it is below the average spending for most of the customers. H0: The average price of an evening entree meal is not significantly different from $20. H1: The average price of an evening entree meal is significantly different from $20. A one sample t-test was conducted on age to evaluate whether the mean price of an entree was significantly different from $20, the accepted mean for the price of an entree meal. The sample mean of 24.09 (SD = 10.11) was significantly different from 20, t (304) = 7.07, p < .01. The results lead to the rejection of null hypothesis since p value is less than 5%. Therefore, it is right to claim that the customers spent an average price of $20 on an evening meal for entree alone. Chef Gaston can therefore price the meal at an average price of $20. H0c: The average number of people living in a household is not significantly different from 4 H1c: The average number of people living in a household is significantly different from 4 A one sample t-test was conducted on age to evaluate whether the mean household number was significantly different from 4, the accepted mean for number of people living in a household. The sample mean of 2.64 (SD = 1.38) was significantly different from 4, t (356) = - 18.57, p > .01. The null hypothesis is rejected since p-value is less than 5% level. This means that on average, customers were from households with 4 people. This is important for Chef Gaston as she can market the restaurant to families expecting to get those that average 4 people. H0d. The average age of customers is not significantly different from 45 years. H1d. The average age of customers is significantly different from 45 years. A one sample t-test was conducted on age to evaluate whether the mean was significantly different from 45, the accepted mean for customers. The sample mean of 45.48 (SD = 9.99) was not significantly different from 45, t (356) = .916, p > .36. The results lead to the acceptance of null hypothesis since p value is more than 5%. The chef can therefore specifically target marketing programs to those aged 45 years. Question 9 Key Restaurant features The results in the table below show that the key restaurant features that are likely to influence consumers likelihood of patronising Chef Gaston’s Restaurant are attractive decor (M = 3.68, SD = 1.51), unique menu (M = 3.60, SD = 1.54), famous chef (M = 3.59, SD = 1.50), wine selection (M = 3.54, SD = 1.50), knowledgeable wait staff (M = 3.54, SD = 1.47), live music (M = 3.48, SD = 1.42), and location with 30 minutes driving distance (M = 3.29, SD = 1.31). N Mean Std. Deviation Attractive Decor 357 3.68 1.514 Unique Menu 357 3.60 1.543 Famous Chef 357 3.59 1.501 Wine Selection 357 3.54 1.501 Knowledgeable Wait Staff 357 3.54 1.470 Live Music 357 3.48 1.419 Located with 30 minutes driving distance 357 3.29 1.313 Upscale Location 357 2.57 1.351 Locally-sourced Ingredients 357 2.43 1.484 Free Valet Parking 357 2.30 1.224 Read More
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