Marketing Research and the Statistical Data - Report Example

MARKETING RESEARCH AND THE STATISTICAL DATA INTERPRETATION In table 0 We have N, standard deviation and mean in which N shows the number of data points which were entered during the survey which was conducted in order to find out the level of satisfaction and customer preferences using different prices in the two hotels. The first point we have Joses Southwestern Cafe with a total of 152 reasonable prices entries while in the second point Santa grill we have a total of 253 prices entries for the research. This shows that some of the values were left not all were entered in the data table. The condition mean is also very essentials elements of the function and must be considered, has it shows the magnitude of the difference between the conditions. In the above table we can see very well that Jose’s southwestern Café has a lower mean compared to the Santa Grill, the Santa grill has a higher price magnitude compared to the Jose’s Southwestern Café has the former has higher mean compared to the later. In the study of the above analysis, one can easily sees quite clear of the significance and magnitude of the above variance and in the median the mode and mean of the data below, indicates that there is a big disparity on the two prices by the two different groups that is Santa grill and the Jose’s southwestern. So there is a significant different in the prices hence affect the types and satisfaction of the two groups of people. In the first scenario of José’s southwestern mean are more than 3 which show that we should not go for the null hypothesis but settle with the alternative hypothesis in the first case and it shows clearly that there is change in the feelings of different people concerning the prices at the Jose’s southwestern Café. While in the closer study of the second scenario where the mean is less than three there is a general change in the feelings of the customers concerning the prices. We should reject the null hypothesis and settle for the alternative hypothesis. The alternative hypothesis is true and the mean differences are significant. This argument is valid for the grouped data since the null hypothesis is rejected. In a closer look of the chi-square analysis if the value is greater or equivalent to the critical value in the analysis, it means there is some significant differences between the groups being studying that is to say. the different between the actual data and the data being studied or expected data, if this is the case then we conclude that the sample we have given is actually supporting the hypothesis of the so difference. But if the chi-square is less than the critical value then we can comfortably say that there is no significant in the difference, and then we can conclude that our sample does not actually support the hypothesis significance In the analysis we have the expected counts of less than 5 while the actual counts should be 13.70 this shows clearly that there is no significant difference in the group which is given In table 1.2 it is clear that the significant level is less than 0.05 that is 0.00 which means there is greater variability in the two samples of data set that were tested the variability in the two conditions are very important and should be considered for decision marking of the types of the customers whether male or female it is usually a bad thing or a bad outcome of the test, this will also help to know the frequency, type and number of customers we expect hence useful in planning. The T- test will actually tell us whether the mean is scientifically significant or not if they were relatively the same. In the above case they are nearly the same so there is no much significance in the two samples of data and will not assist much in decision making. In table 1.3 below. There is no statistical significance since the 2-tailed t-test is the same so the statistical significance difference between the two conditions does not exist. The Sig. (2-Tailed) values in the table are 0.00 this value is actually less than .05. Because of this, we are concluding that there is a statistically significant difference between the mean of the sample test, the number of customers visiting the cafeteria in terms of female and male are different at any single minutes this information is also useful for management purposes in designing the general outlook of the cafeteria depending with the kind of visitors expected. When looking at the table1.4. Below. It is seen that the significance level between the groups is 0.70 which is higher than 0.5 which is the stated value of the test. This shows that there is no statistical significance in the level of satisfactions of the group. The likeliness of the return of the customer’s significant level is 0.8 which is much higher than the expected value which is 0.05 in the ANOVA table which also shows that there is no statistical difference in the group data of the two samples of male and female. In summary, the null hypothesis should be rejected and the alternative hypothesis is the appropriate for the study of the customer satisfaction and the type of the customer who is going to visit the cafeteria. The time interval or frequency of the visit by different customers is determined by the price of the hotel and in turn influences the type of the customer who is to visit which cafeteria and at what time. The validity of our conclusion depends on the hypothesis which was taken into consideration and which one was rejected, since we rejected null hypothesis, our conclusion is valid. One-Sample Statistics Favorite Mexican Restaurant N Mean Std. Deviation Joses Southwestern Café X16 -- Reasonable Prices 152 4.12 .906 Santa Fe Grill X16 -- Reasonable Prices 253 4.47 1.384 Table1.0 Statistics X25 -- Frequency of Eating at . . . ?? Joses Southwestern Café N Valid 152 Missing 0 Mean 3.79 Median 4.00 Mode 3 Santa Fe Grill N Valid 253 Missing 0 Mean 2.92 Median 3.00 Mode 2 Table1.1 Independent Samples Test Favorite Mexican Restaurant Levenes Test for Equality of Variances F Sig. Santa Fe Grill X22 – Satisfaction Equal variances assumed 19.800 .000 Equal variances not assumed Table 1.2 Independent Samples Test Favorite Mexican Restaurant t-test for Equality of Means T df Sig. (2-tailed) Santa Fe Grill X22 – Satisfaction Equal variances assumed 3.882 251 .000 Equal variances not assumed 4.241 179.954 .000 Table1.3 ANOVA X32 – Gender F Sig. Male X22 -- Satisfaction Between Groups .149 .700 Within Groups Total X23 -- Likely to Return Between Groups .058 .810 Within Groups Total X24 -- Likely to Recommend Between Groups 19.275 .000 Within Groups Total Female X22 -- Satisfaction Between Groups 174.585 .000 Within Groups Total X23 -- Likely to Return Between Groups 152.591 .000 Within Groups Total X24 -- Likely to Recommend Between Groups 134.242 .000 Within Groups Total Table1.4 Reference www.meandeviation.com/tutorials/stats/notes/booklist.htmlCached - Similar You +1d this publicly. Undo Experiment, Design and Statistics in Psychology: Colin Robson. Pelican Books. 1983. (174 pages): Describes itself as a cook book.. Step-by-step procedures Statistical conclusion validity by Karl L. Wuensh. 2003. Read More