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Individual Data Analysis - Michael Jenkins - Assignment Example

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The paper "Individual Data Analysis - Michael Jenkins " discusses that Michael can use the data collected related to the monthly spending of the customers to find their preferences regarding the décor entrée, desserts, water view, formal wear of the waiting staff and the type of entertainment…
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Individual Data Analysis - Michael Jenkins
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? Finance and Accounting of the of the Table of Contents Introduction 3 Preliminary Analysis 4 Frequencies of categorical variable 4 Descriptive statistics 6 Data Screening 7 Hypothesis testing 10 Techniques used 13 Statistical and non-statistical interpretation 13 Summary and Discussion 15 Recommendation 16 Appendix 19 Introduction This case is about Michael Jenkins who works as a sales representative in a restaurant and dreams of owning a restaurant business of his own. He has saved substantial amount and has approached his banker with certain financial figures. Michael and his banker both agreed on the fact that he has got enough capital to seriously contemplate investment and make his dreams come true. Michael had dreamt regarding a restaurant, with the finest features starting from the menu to the elegant atmosphere. Although he has enough knowledge needed to start such an upscale restaurant, he is unsure about the demand for such a restaurant in the city. The city had a population of nearly 500,000 but he could not provide any assurance regarding the taste or the income which would generate the demand for his restaurant. In such a situation, Michael requires to collect some additional information, on the basis of which he will succeed in promoting his restaurant properly and make the design, choices and price as per the preferable choice of the customers. In this context, the project aims to answer the questions raised by Michael and suggest him the most suitable way that he should choose to make his new business intervention profitable. The questions are as follows: Is there sufficient demand for such an upscale restaurant in the city? How much price are the patrons or the potential customers willing to pay? What should be the operating and design characteristics of the store? Where should the restaurant be located in the city? What should be the promotional strategy that the organization should follow? In order to find the answers to these questions, the study intends to frame certain hypotheses and find the answers to the questions by accepting or rejecting those. The study also uses descriptive analysis and frequencies to facilitate the process of finding the answers to the questions. Finally, the paper will be providing the necessary recommendations to Michael. Preliminary Analysis In the preliminary analysis, descriptive analysis and analysis using the frequencies is done and it is focused on finding answers to the questions raised by Michael. Frequencies of categorical variable The frequencies of the categorical variable when performed, it firstly found that the people of the metropolitan city where Michael is intending to open his business, about 100 percent of the people do eat in this type of upscale restaurant at least once in every two weeks. The analysis also revealed that maximum people is seen to pay $110 towards their meal in the restaurant for each month, which is unlike the expectation of Michael. When the survey participants were asked for their opinion on the average price charged for an evening meal entree, they are found to spend $16 for evening meal entree itself (See Appendix I). The analysis shows that about 96.3 percent of the respondents watch radio. Among those 96.3 percent, maximum of the respondents are found to be listening to rock music. The next higher percent listens to news or the talk shows. Among the participants of the survey, about 89 percent of the respondents are found to be the viewers of the local news channel. Out of these respondents, maximum percent is the viewers of 10:00 news. Among the 94.5 percent of the respondents who are the readers of newspaper, a majority of the respondents are more interested in the local news. Therefore, the overall analysis reveals that a majority of the sample who participated in the study are interested in newspaper and radio as their most preferable media which they listen to often. The least preferred one is television. Thus, it can be suggested that among these three, Michael can choose newspaper and radio as the two media to use for promoting his new restaurant. He can print advertisements in the local news section of the newspaper. When the data are analyzed to see whether the patrons in the locality prefer waterfront view, about 35.3 percent of the respondents somewhat preferred, while about 24 percent of the respondents very strongly preferred the waterfront view. When the study aimed to measure whether the driving time that the respondents preferred is less than 30 minutes, it is seen that a majority of the respondents does not prefer to drive 30 minutes to reach the restaurant. When the respondents were asked whether they prefer formally dressed waiting staff in tuxedos, about 34.8 percent and 32.8 percent of the respondents did not prefer strongly and somewhat preferred respectively. Again, the survey also found that 39.8 percent and 26 percent of the respondents do not prefer strongly and somewhat do not prefer any unusual type of desserts, respectively. The survey also revealed that maximum of the respondents does not very strongly prefer large variety of entrees. A majority of the respondents also prefer somewhat and very strongly the unusual entrees. These two findings imply that the entrees should be kept simple since neither the patrons are in favor of unusual entrees nor do they like large amount of entrees. When it comes to deciding about the decor of the restaurant, whether to keep it simple or elegant, the survey showed that most of the respondents somewhat prefer or very strongly prefer that the decor of the restaurant should be kept simple and at the same time, a majority of the respondents are either very strongly or somewhat against the elegancy in decor. When it came to their preference regarding type of entertainment, string quartet is not preferred by maximum of the patrons whereas they prefer Jazz combo heavily. When the survey evaluated the characteristics of the participants, most of the respondents were observed to be born in the year 1960. Scrutiny of the education level showed that 59.5 percent of the respondents had bachelor’s degree and 21.5 percent had a master’s degree. A higher proportion of the respondents were married and some were single. The respondents of the survey mostly belonged to a family of two but a significant number of respondents were also from family sizes of one and three, which cannot be ignored. The frequency revealed that 49 percent of the respondents were female and 51 percent of the respondents were male. The maximum of the survey participants had an income of $62500. However, the frequency analysis suggests that most of the respondents are not interested in this new type of restaurant. Descriptive statistics The results of the descriptive statistics provide the minimum, maximum, mean and standard deviation results of the variables that are being studied (Mendenhall, Beaver & Beaver, 2013; C.F. Lee, J.C. Lee & A.C. Lee, 2013; Laudanski, 2012; Sims, 2000; Kumar & Chaudhary, 2010; Salkind, 2004; Gravetter & Wallnau, 2007; R.B. Burns & R. Burns, 2008; Mann, 2007; Heiman, 2010). Following are the results of the descriptive statistics: An average number of respondents are seen to visit this type of up market restaurant. The average amount spend per month towards this type of restaurant is $150.05, which suggests that Michael cannot expect the patrons to spend $200 per month. Moreover, there is a huge difference between the maximum and minimum range (See Appendix II). Michael had expected that the patrons will be paying $18 for the entrees, which is equivalent to the outcome of the descriptive analysis. However, the maximum and the minimum range seem to differ over a wider range. The descriptive statistics also show that the year in which most of the respondents are born is 1957. The recorded income of average number of respondents is $76469. However, the statistics also reveals a significant amount of difference between the maximum and the minimum income level. Data Screening Data screening is one of the important steps of data management. In this step, the missing data and the outliers that is the data with unusual values are detected (Kirch, 2008; Dasgupta, 2006; Hatcher, 1994; Dawdy, Lichty & Bergmann, 1972). In this process, the collected data except the data which is represented in certain scale like, Linker scale, or the data that has a response of only ‘yes’ and ‘no’, are excluded. In this case, four data are considered on which data screening will get done like, assessing the amount of dollar spent. The data related to the amount of dollar that is spent per month is seen to be nearer to the line of normality and is devoid of too much deviation (See Figure 1). The average amount spent on the evening meal entree also shows less deviation from the line of normality (See figure 2). The case is same for year born and recorded income of the respondents (See figure 3 and 4). Figure 1 Figure 2 Figure 3 Figure 4 Hypothesis testing Here follows the ten hypotheses (Romano, 2006; Shi & Tao, 2008; Wilcox, 2012; Koch, 1999; Poletiek, 2013; Haroutunian & Harutyunyan, 2008; Fiedler, 2004): For the first question where Michael is trying to find whether the patrons are willing to pay $18 for the entrees, the hypotheses are as follows: Alternate hypothesis (H1): The potential patrons are willing to pay till $18 for the entrees. Null hypothesis (H0): The potential patrons are not willing to pay $18 for the entrees. In order to find the answer whether Michael can expect all the patrons to pay $200 on an average per month towards their food: Alternate hypothesis (H2): All the patrons will pay $200 on an average per month towards their food. Null hypothesis (H0): All the patrons are not willing to pay $200 on an average per month towards their food. In order to check the potential postcode area for the restaurant, the hypothesis is: Alternative hypothesis (H3): There is a relationship between the likelihood towards attending the restaurant and the post code. Null hypothesis (H0): There is no relationship between the likelihood towards attending the restaurant and the post code. To check whether the average monthly spending differs among the patron on the basis of their income, the hypotheses are framed as follows: Alternative hypothesis (H4): The average monthly spending of the patrons has a link with their level of income. Null hypothesis (H0): The average monthly spending of the patrons does not have any link with their level of income. In order to find whether the patrons like water view or want to drive for less than 30 minutes to reach the restaurant, the following hypothesis should be tested: Alternative hypothesis (H5): The patrons prefer water view or less than 30 minutes drive. Null hypothesis (H0): The patrons do not prefer water view or less than 30 minutes drive. In order to check whether the customers prefers unusual desserts or unusual entrees or both at the same time, the following hypothesis is considered: Alternative hypothesis (H6): The patrons prefer unusual desserts or unusual entrees or both at the same time. Null hypothesis (H0): The patrons do not prefer unusual desserts or unusual entrees or both at the same time. In order to check which section of the newspaper serves as the most potential section for Michael to advertise his new up market restaurant, the following hypothesis is tested: Alternative hypothesis (H7): There is a relationship between the likely hood of patrons and the section of newspaper they read. Null hypothesis (H0): There is no relationship between the likely hood of patrons and the section of newspaper they read. In order to check whether the monthly spending depends on the variables like age, family size and gender, the following hypothesis is framed: Alternative hypothesis (H8): The monthly spending of the patrons is directly linked with restaurant preference variables, age, family size and gender. Null hypothesis (H0): The monthly spending of the patrons is not directly linked with restaurant preference variables, age, family size and gender. Alternative hypothesis (H9): Family size influences whether a patron is probable or not probable. Null hypothesis (H0): Family size does not influence whether a patron is probable or not probable. Alternative hypothesis (H10): There is relationship between marital status and a patron being probable. Null hypothesis (H0): There is no relationship between marital status and a patron being probable. Techniques used In case of bi-variate analysis, paired t-test is used where two variables are compared and also in cases where one variable is the partner of the other. This test considers the variation of the values within each sample and then generates a single number called t-value. This t-value is used for analysis. In this case paired t-test is used where two independent variables are compared like in case of all the hypotheses except 8. In case of multivariate analysis, linear regression is used where there are separate set of dependent and independent variables. After conducting this, the F value is used for analysis. In this case linear regression is used for hypothesis 8, since it has one independent variable and a set of dependent variables (Cassens, 1992; Kerr, Hall & Kozub, 2002; Milton & Arnold, 2006; Peck, R., Olsen & Devore, n.d.; Berkman & Reise, 2011; Goldschmied, 2007; Peck & Devore, 2010; Verma, 2011; Utts & Heckard, 2005). Statistical and non-statistical interpretation The hypotheses are tested using t-test which is two tailed test on a sample size of 400. This signifies that the degree of freedom for all the tests is 399. For the first hypothesis, the critical value, at 399 degree of freedom and level of significance of 0.05, is 1.965 (MedCalc Software, 2013). When this value is compared to the t value, which is -31.855, it is seen that the critical value is much higher (See Appendix III). Therefore, for the first case the null hypothesis is accepted and the alternative hypothesis is rejected. Hence, the potential patrons are not willing to pay $18. For the second hypothesis, it is again seen that the t value is -32.156, which is again much lower than the critical value (See Appendix IV). This means that in the second case, the null hypothesis is accepted which signifies that patrons are not willing to spend $200. In the third case, the t-value is 3.64, which is much higher than the critical value which is 1.965 (See Appendix V). This implies that the null hypothesis is rejected and the alternative hypothesis is accepted. Hence, there is a relationship between the post code of an area and the likelihood of visiting a restaurant. In the fourth case, the t-test has given a t-value of 32.003, which is much higher than the critical value (See Appendix VI). This signifies that in this case, the alternative hypothesis is accepted and the null hypothesis is rejected. Hence, there exists a relationship between amount of dollars spent in the restaurant and the household income including tax. The fifth case has two variables which are whether the patrons would prefer water view or whether they prefer less than 30 minutes drive, so the t-test has been conducted in two pairs. In the first pair, that is whether the patrons prefer water view, the t value is -36.297, which is much lower than the critical value (See Appendix VII). Again for the second pair, the t-value is -26.316, which is again lower than the critical value. Both the cases suggest that the null hypothesis is accepted. Hence, it can be concluded that in the fifth case, the patrons neither prefer water view nor less than 30 minutes drive. In the sixth case, the hypothesis again tests with two variables. The first pair which tests whether the patrons prefer unusual desserts, the t value is -18.593 which is much lower than the critical value (See Appendix VIII). Also, for the other pair, the t value is much lower than the critical value. So it can be concluded that the null hypothesis is accepted, thereby indicating that the patrons do not favors unusual desserts, unusual entrees or both at the same time. In case of the seventh hypothesis, the value of the t-test is lower than the critical value (See Appendix IX). Hence, in this case also, the alternate hypothesis is rejected. There is no relationship between the potential patrons and the section of newspaper that they prefer. For testing the eighth hypothesis, linear regression is conducted, which gives an F value of 103.209, which is much higher (See Appendix X). Thus, the alternative hypothesis is accepted, which means that the monthly spending of the patrons is directly linked with restaurant preference variables like, age, family size and gender. In the ninth case where it is tested whether the probable patron has a link with the family size, the t-value is seen to be -12.028 which is much lower than the critical value (See Appendix XI). Hence, the null hypothesis is rejected, which signifies that there is no relationship between the probable patron of the restaurant and the family size. Again in the last case, where the test checks whether there is any relationship between the probable patron and the marital status, the t-value of the t-test is -3.72 (See Appendix XII). This indicates that the t value is much lower than the critical value, thereby signifying that the null hypothesis is accepted. Hence, it can be concluded that there is no relationship between probable patron and marital status. Summary and Discussion In the hypothesis testing only in case of the third, fourth and eighth, the alternative hypothesis is accepted and in rest of the cases, it is rejected. This implies that Michael can expect that the post code of the area has a direct relationship with the chances of drawing potential customers. On the other hand, he can also expect that the customers with a higher household income will show a greater amount of interest to spend larger amounts on the up market restaurants. Michael can also use the data collected related to the monthly spending of the customers to find their preferences regarding the decor entree, desserts, water view, formal wear of the waiting staff and the type of entertainment. The spending of the customers is also influenced by the family size, gender and age of the customers. Recommendation The findings of the data analysis report recommend that: Although people are habituated to go to such up market restaurants, they are not willing to have a new restaurant of the same kind. Contrary to the statistical analysis which shows that Michael should not expect customers to spend $18, the preliminary analysis suggests just the opposite. While deciding the decor and other operating characteristics, Michael can consider the income level of the customers as the deciding factor. Thus, the type of customers that he would target will be the deciding factor of these features. Since high income customers are the best potential target for such an up market restaurant, Michael should open his stores in the post code area where he finds residents with such earnings. Post code B and C are seen to be the potential areas where Michael should open his restaurant. References Berkman, E.T. & Reise, S.P. (2011). A conceptual guide to statistics using SPSS. London: SAGE. Burns, R.B. & Burns, R. (2008). Business research methods and statistics using SPSS. London: SAGE. Cassens, B.J. (1992). Preventive medicine and public health. New York: Lippincott Williams & Wilkins. Dasgupta, S. (2006). Encyclopedia of virtual communities and technologies. New Delhi: Idea Group Inc. Dawdy, D.R., Lichty, R.W. & Bergmann, J.M. (1972). United States Geological Survey Professional Paper. Washington: U.S. Government Printing Office. Fiedler, K. (2004). Stereotyping as inductive hypothesis testing. New Jersey: Psychology Press. Goldschmied, N. (2007). The appeal of the underdog: Definition of the construct and implications for the self. Ann Arbor: ProQuest. Gravetter, F.J. & Wallnau, L.B. (2007). Statistics for the behavioral sciences. Connecticut: Cengage Learning. Haroutunian, M.E. & Harutyunyan, A.N. (2008). Reliability criteria in information theory and in statistical hypothesis testing. Massachusetts: Now Publishers Inc. Hatcher, L. (1994). A step-by-step approach to using the SAS system for factor analysis and structural equation modeling. North Carolina: SAS Institute. Heiman, G.W. (2010). Basic statistics for the behavioral sciences. Connecticut: Cengage Learning. Kerr, A.W., Hall, H.K. & Kozub, S.A. (2002). Doing statistics with SPSS. London: SAGE. Kirch, W. (2008). Encyclopedia of public health. Berlin: Springer. Koch, K.R. (1999). Parameter estimation and hypothesis testing in linear models. Berlin: Springer. Kumar, A. & Chaudhary, A. (2010). Descriptive statistics. Meerut: Krishna Prakashan Media. Laudanski, L.M. (2012). Between certainty and uncertainty: statistics and probability in five units with notes on historical origins and illustrative numerical examples. Berlin: Springer. Lee, C-F., Lee, J.C. & Lee, A.C. (2013). Statistics for business and financial economics. Berlin: Springer. Mann, P.M. (2007). Introductory statistics. 5th Ed. New Jersey: John Wiley & Sons. MedCalc Software. (2013). Values of the t-distribution (two-tailed). Retrieved from Mendenhall, W. III; Beaver, R.J. & Beaver, B.M. (2013). Introduction to probability and statistics. 14th Ed. Connecticut: Cengage Learning. Milton, J.S. & Arnold, J.C. (2006). Introduction to probability & statistics. New Delhi: Tata McGraw-Hill Education. Peck, R. & Devore, J.L. (2010). Statistics: The exploration & analysis of data. Connecticut: Cengage Learning. Peck, R., Olsen, C. & Devore, J. (n.d.). Introduction to statistics and data analysis. Connecticut: Cengage Learning. Poletiek, F.H. (2013). Hypothesis-testing behaviour. New Jersey: Psychology Press. Romano, J.P. (2006). Testing statistical hypotheses. Berlin: Springer. Salkind, N.J. (2004). Statistics for people who (think they) hate statistics. London: SAGE. Shi, N-Z. & Tao, J. (2008). Statistical hypothesis testing: Theory and methods. London: World Scientific. Sims, R.L. (2000). Bivariate data analysis: A practical guide. New York: Nova Publishers. Utts, J.M. & Heckard, R.F. (2005). Statistical ideas and methods. Connecticut: Cengage Learning. Verma, J.P. (2011). Statistical methods in sports & physical education. New Delhi: Tata McGraw-Hill Education. Wilcox, R.R. (2012). Introduction to robust estimation and hypothesis testing. California: Academic Press. Appendix I: Frequency Frequency Table Do you eat at this type of restaurant at least once every two weeks? Frequency Percent Valid Percent Cumulative Percent Valid Yes 400 100.0 100.0 100.0 How many total dollars do you spend per month in restaurants (for your meals only)? Frequency Percent Valid Percent Cumulative Percent Valid $5.00 2 .5 .5 .5 $6.00 3 .8 .8 1.3 $7.00 3 .8 .8 2.0 $8.00 2 .5 .5 2.5 $9.00 2 .5 .5 3.0 $10.00 6 1.5 1.5 4.5 $11.00 6 1.5 1.5 6.0 $12.00 3 .8 .8 6.8 $13.00 5 1.3 1.3 8.0 $14.00 8 2.0 2.0 10.0 $15.00 3 .8 .8 10.8 $16.00 3 .8 .8 11.5 $17.00 2 .5 .5 12.0 $18.00 5 1.3 1.3 13.3 $19.00 5 1.3 1.3 14.5 $20.00 2 .5 .5 15.0 $65.00 1 .3 .3 15.3 $70.00 1 .3 .3 15.5 $75.00 7 1.8 1.8 17.3 $80.00 9 2.3 2.3 19.5 $85.00 7 1.8 1.8 21.3 $90.00 10 2.5 2.5 23.8 $95.00 10 2.5 2.5 26.3 $100.00 5 1.3 1.3 27.5 $105.00 10 2.5 2.5 30.0 $110.00 18 4.5 4.5 34.5 $115.00 7 1.8 1.8 36.3 $120.00 15 3.8 3.8 40.0 $125.00 15 3.8 3.8 43.8 $130.00 10 2.5 2.5 46.3 $135.00 16 4.0 4.0 50.3 $140.00 15 3.8 3.8 54.0 $145.00 16 4.0 4.0 58.0 $150.00 13 3.3 3.3 61.3 $155.00 4 1.0 1.0 62.3 $160.00 15 3.8 3.8 66.0 $165.00 12 3.0 3.0 69.0 $170.00 4 1.0 1.0 70.0 $180.00 2 .5 .5 70.5 $200.00 5 1.3 1.3 71.8 $210.00 6 1.5 1.5 73.3 $215.00 7 1.8 1.8 75.0 $220.00 8 2.0 2.0 77.0 $225.00 8 2.0 2.0 79.0 $230.00 6 1.5 1.5 80.5 $235.00 4 1.0 1.0 81.5 $240.00 1 .3 .3 81.8 $245.00 8 2.0 2.0 83.8 $250.00 5 1.3 1.3 85.0 $255.00 4 1.0 1.0 86.0 $260.00 7 1.8 1.8 87.8 $265.00 2 .5 .5 88.3 $270.00 3 .8 .8 89.0 $275.00 6 1.5 1.5 90.5 $276.00 2 .5 .5 91.0 $280.00 4 1.0 1.0 92.0 $285.00 3 .8 .8 92.8 $290.00 3 .8 .8 93.5 $295.00 2 .5 .5 94.0 $300.00 4 1.0 1.0 95.0 $310.00 1 .3 .3 95.3 $315.00 1 .3 .3 95.5 $320.00 1 .3 .3 95.8 $340.00 1 .3 .3 96.0 $345.00 1 .3 .3 96.3 $350.00 2 .5 .5 96.8 $355.00 1 .3 .3 97.0 $360.00 3 .8 .8 97.8 $370.00 1 .3 .3 98.0 $375.00 1 .3 .3 98.3 $380.00 1 .3 .3 98.5 $390.00 1 .3 .3 98.8 $400.00 2 .5 .5 99.3 $450.00 3 .8 .8 100.0 Total 400 100.0 100.0 How likely would it be for you to patronize this restaurant (new upscale restaurant)? Frequency Percent Valid Percent Cumulative Percent Valid Very Unlikely 52 13.0 13.0 13.0 Somewhat Unlikely 77 19.3 19.3 32.3 Neither Likely Nor Unlikely 161 40.3 40.3 72.5 Somewhat Likely 38 9.5 9.5 82.0 Very Likely 72 18.0 18.0 100.0 Total 400 100.0 100.0 What would you expect an average evening meal entree item alone to be priced? Frequency Percent Valid Percent Cumulative Percent Valid $6.00 2 .5 .6 .6 $7.00 7 1.8 2.1 2.6 $8.00 15 3.8 4.4 7.1 $9.00 11 2.8 3.2 10.3 $10.00 20 5.0 5.9 16.2 $11.00 19 4.8 5.6 21.8 $12.00 25 6.3 7.4 29.1 $13.00 19 4.8 5.6 34.7 $14.00 24 6.0 7.1 41.8 $15.00 22 5.5 6.5 48.2 $16.00 27 6.8 7.9 56.2 $17.00 21 5.3 6.2 62.4 $18.00 12 3.0 3.5 65.9 $19.00 1 .3 .3 66.2 $20.00 2 .5 .6 66.8 $21.00 5 1.3 1.5 68.2 $22.00 8 2.0 2.4 70.6 $23.00 6 1.5 1.8 72.4 $24.00 11 2.8 3.2 75.6 $25.00 7 1.8 2.1 77.6 $26.00 10 2.5 2.9 80.6 $27.00 7 1.8 2.1 82.6 $28.00 5 1.3 1.5 84.1 $29.00 5 1.3 1.5 85.6 $30.00 11 2.8 3.2 88.8 $32.00 4 1.0 1.2 90.0 $33.00 5 1.3 1.5 91.5 $35.00 6 1.5 1.8 93.2 $36.00 1 .3 .3 93.5 $37.00 2 .5 .6 94.1 $38.00 4 1.0 1.2 95.3 $40.00 4 1.0 1.2 96.5 $43.00 1 .3 .3 96.8 $45.00 3 .8 .9 97.6 $48.00 1 .3 .3 97.9 $50.00 5 1.3 1.5 99.4 $55.00 1 .3 .3 99.7 $60.00 1 .3 .3 100.0 Total 340 85.0 100.0 Missing $999.00 60 15.0 Total 400 100.0 Would you describe yourself as one who listens to the radio? Frequency Percent Valid Percent Cumulative Percent Valid Yes 385 96.3 96.3 96.3 No 15 3.8 3.8 100.0 Total 400 100.0 100.0 To which type of radio programming do you most often listen? Frequency Percent Valid Percent Cumulative Percent Valid Country&Western 66 16.5 17.1 17.1 Easy Listening 78 19.5 20.3 37.4 Rock 159 39.8 41.3 78.7 Talk/News 82 20.5 21.3 100.0 Total 385 96.3 100.0 Missing 99 15 3.8 Total 400 100.0 Would you describe yourself as a viewer of TV local news? Frequency Percent Valid Percent Cumulative Percent Valid Yes 356 89.0 89.0 89.0 No 44 11.0 11.0 100.0 Total 400 100.0 100.0 Which newscast do you watch most frequently? Frequency Percent Valid Percent Cumulative Percent Valid 7:00 am News 32 8.0 9.0 9.0 Noon News 1 .3 .3 9.3 6:00 pm News 129 32.3 36.2 45.5 10:00 pm News 194 48.5 54.5 100.0 Total 356 89.0 100.0 Missing 99 44 11.0 Total 400 100.0 Do you read the newspaper? Frequency Percent Valid Percent Cumulative Percent Valid Yes 378 94.5 94.5 94.5 No 22 5.5 5.5 100.0 Total 400 100.0 100.0 Which section of the local newspaper would you say you read most frequently? Frequency Percent Valid Percent Cumulative Percent Valid Editorial 52 13.0 13.7 13.7 Business 65 16.3 17.2 30.9 Local 118 29.5 31.1 62.0 Classifieds 57 14.3 15.0 77.0 Life, Health & Entertainment 87 21.8 23.0 100.0 Total 379 94.8 100.0 Missing 99 21 5.3 Total 400 100.0 Prefer Waterfront View Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 45 11.3 11.3 11.3 Somewhat Not Prefer 75 18.8 18.8 30.0 Neither Prefer Nor Not Prefer 43 10.8 10.8 40.8 Somewhat Prefer 141 35.3 35.3 76.0 Very Strongly Prefer 96 24.0 24.0 100.0 Total 400 100.0 100.0 Prefer Drive Less than 30 Minutes Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 72 18.0 18.0 18.0 Somewhat Not Prefer 141 35.3 35.3 53.3 Neither Prefer Nor Not Prefer 68 17.0 17.0 70.3 Somewhat Prefer 63 15.8 15.8 86.0 Very Strongly Prefer 56 14.0 14.0 100.0 Total 400 100.0 100.0 Prefer Formal Waitstaff Wearing Tuxedos Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 139 34.8 34.8 34.8 Somewhat Not Prefer 131 32.8 32.8 67.5 Neither Prefer Nor Not Prefer 10 2.5 2.5 70.0 Somewhat Prefer 45 11.3 11.3 81.3 Very Strongly Prefer 75 18.8 18.8 100.0 Total 400 100.0 100.0 Prefer Unusual Desserts Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 159 39.8 39.8 39.8 Somewhat Not Prefer 104 26.0 26.0 65.8 Neither Prefer Nor Not Prefer 17 4.3 4.3 70.0 Somewhat Prefer 55 13.8 13.8 83.8 Very Strongly Prefer 65 16.3 16.3 100.0 Total 400 100.0 100.0 Prefer Large Variety of Entrees Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 145 36.3 36.3 36.3 Somewhat Not Prefer 97 24.3 24.3 60.5 Neither Prefer Nor Not Prefer 38 9.5 9.5 70.0 Somewhat Prefer 63 15.8 15.8 85.8 Very Strongly Prefer 57 14.3 14.3 100.0 Total 400 100.0 100.0 Prefer Unusual Entrees Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 171 42.8 42.8 42.8 Somewhat Not Prefer 86 21.5 21.5 64.3 Neither Prefer Nor Not Prefer 23 5.8 5.8 70.0 Somewhat Prefer 50 12.5 12.5 82.5 Very Strongly Prefer 70 17.5 17.5 100.0 Total 400 100.0 100.0 Prefer Simple Decor Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 64 16.0 16.0 16.0 Somewhat Not Prefer 56 14.0 14.0 30.0 Neither Prefer Nor Not Prefer 13 3.3 3.3 33.3 Somewhat Prefer 120 30.0 30.0 63.3 Very Strongly Prefer 147 36.8 36.8 100.0 Total 400 100.0 100.0 Prefer Elegant Decor Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 177 44.3 44.3 44.3 Somewhat Not Prefer 92 23.0 23.0 67.3 Neither Prefer Nor Not Prefer 11 2.8 2.8 70.0 Somewhat Prefer 63 15.8 15.8 85.8 Very Strongly Prefer 57 14.3 14.3 100.0 Total 400 100.0 100.0 Prefer String Quartet Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 130 32.5 32.5 32.5 Somewhat Not Prefer 110 27.5 27.5 60.0 Neither Prefer Nor Not Prefer 40 10.0 10.0 70.0 Somewhat Prefer 69 17.3 17.3 87.3 Very Strongly Prefer 51 12.8 12.8 100.0 Total 400 100.0 100.0 Prefer Jazz Combo Frequency Percent Valid Percent Cumulative Percent Valid Very Strongly Not Prefer 25 6.3 6.3 6.3 Somewhat Not Prefer 50 12.5 12.5 18.8 Neither Prefer Nor Not Prefer 77 19.3 19.3 38.0 Somewhat Prefer 118 29.5 29.5 67.5 Very Strongly Prefer 130 32.5 32.5 100.0 Total 400 100.0 100.0 Year Born Frequency Percent Valid Percent Cumulative Percent Valid 1928 1 .3 .3 .3 1929 1 .3 .3 .5 1930 2 .5 .5 1.0 1931 2 .5 .5 1.5 1932 2 .5 .5 2.0 1933 1 .3 .3 2.3 1934 2 .5 .5 2.8 1935 3 .8 .8 3.5 1936 3 .8 .8 4.3 1937 1 .3 .3 4.5 1938 2 .5 .5 5.0 1942 1 .3 .3 5.3 1943 3 .8 .8 6.0 1944 3 .8 .8 6.8 1945 7 1.8 1.8 8.5 1946 10 2.5 2.5 11.0 1947 15 3.8 3.8 14.8 1948 16 4.0 4.0 18.8 1949 10 2.5 2.5 21.3 1950 12 3.0 3.0 24.3 1951 15 3.8 3.8 28.0 1952 10 2.5 2.5 30.5 1953 13 3.3 3.3 33.8 1954 8 2.0 2.0 35.8 1955 7 1.8 1.8 37.5 1956 9 2.3 2.3 39.8 1957 15 3.8 3.8 43.5 1958 20 5.0 5.0 48.5 1959 15 3.8 3.8 52.3 1960 23 5.8 5.8 58.0 1961 19 4.8 4.8 62.8 1962 18 4.5 4.5 67.3 1963 9 2.3 2.3 69.5 1964 14 3.5 3.5 73.0 1965 22 5.5 5.5 78.5 1966 14 3.5 3.5 82.0 1967 13 3.3 3.3 85.3 1968 19 4.8 4.8 90.0 1969 15 3.8 3.8 93.8 1970 5 1.3 1.3 95.0 1971 5 1.3 1.3 96.3 1972 3 .8 .8 97.0 1973 5 1.3 1.3 98.3 1974 2 .5 .5 98.8 1975 5 1.3 1.3 100.0 Total 400 100.0 100.0 What is your highest level of education? Frequency Percent Valid Percent Cumulative Percent Valid Less than High School 11 2.8 2.8 2.8 Some High School 14 3.5 3.5 6.3 High School Graduate 14 3.5 3.5 9.8 Some College (No Degree) 14 3.5 3.5 13.3 Associate Degree 14 3.5 3.5 16.8 Bachelor's Degree 238 59.5 59.5 76.3 Master's Degree 86 21.5 21.5 97.8 Doctorate Degree 9 2.3 2.3 100.0 Total 400 100.0 100.0 What is your marital status? Frequency Percent Valid Percent Cumulative Percent Valid Single 93 23.3 23.3 23.3 Married 272 68.0 68.0 91.3 Other (Divorced, Widow, etc.) 35 8.8 8.8 100.0 Total 400 100.0 100.0 Including children under 18 living with you, what is your family size? Frequency Percent Valid Percent Cumulative Percent Valid 1 99 24.8 24.8 24.8 2 106 26.5 26.5 51.3 3 98 24.5 24.5 75.8 4 61 15.3 15.3 91.0 5 24 6.0 6.0 97.0 6 9 2.3 2.3 99.3 7 3 .8 .8 100.0 Total 400 100.0 100.0 Please check the letter that includes the Post Code in which you live (coded by letter). Frequency Percent Valid Percent Cumulative Percent Valid A (1 & 2) 20 5.0 5.0 5.0 B (3, 4, & 5) 120 30.0 30.0 35.0 C (6, 7, 8, & 9) 220 55.0 55.0 90.0 D (10, 11, & 12) 40 10.0 10.0 100.0 Total 400 100.0 100.0 Which of the following categories best describes your before tax household income? Frequency Percent Valid Percent Cumulative Percent Valid Read More
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