Regression Analysis of Body Shock Ltd - Case Study Example

HARVARD STYLE) By PART Body shock Ltd. is a nationwide chain of fitness centers with giving many facilities for their customers in most major towns in the UK. The Company CEOs and HR management believe strongly in the role of local advertising to stimulate their services and thus spend money with local radio stations and papers. The Company employs both radio and newspaper services for advancing their work and experience. In my peak of view Newspapers advertisement is much more effective and considering for enhancing their line of work. As newspaper reading habit in the UK is much more than people like to listen radio. In UK reading habit is addicted by the great unwashed. If Company advertise their services in the newspapers there can be two benefits first people read more newspaper as compare to listen radio and secondly, if they require to revise or giving consultation for that advertisement can access that easily. Here are some work sample with graphs and histograms to show that Yes! My point of view of advertising in newspapers is more effective than that to listen radio. At first we will show the descriptive statistics, which means explanation of data features in the study. Plane summaries are provided regarding the measures and the sample. With the help of graphic analysis, base for all the qualitative data is provided (William M.K. Trochim, 2006). In the descriptive statistics the news has a maximum number up to 12 thousand, whereas the radio maximum value is up to 11 thousand. The result again emphasizes my analysis that advertisement in newspapers is much more effective than radio. The data taken is about 45 values whose mean value again emphasizes on newspapers. Today the second evidence will be accepted from the boxplot values as we have withdrawn from these above taken values and will demonstrate how the newspaper advertisement is much safer and more effective than listen to the wireless. A technique to summarize the data which is measured on the interval scale is the boxplot. The shape of the distribution is expressed by this type of graph. Most extremes values of the set of data, its variability and central values are presented by the picture (Valerie J. Easton and John H. McColls 1998). If we examine the boxplot graph closely, we can catch the radio box and its upper limit is less than 9000 value, whereas the news box and its upper value are above 9000. Which clearly implies that newspapers upper limit is high that to radio. This again justifies my point and analysis techniques as well. The boxplot and the Histogram in both statistical analyses, we clearly examine and can suggest to the troupe that they should be made to the company expenditure on news greater than the quantity of money spent on radio. The data on news skews more to the right, due to the fact that the mean and median for news are higher than for the tuner radio. People or can say audience for the advertisement is more emphasis on intelligence (reading material) rather than wireless (radio). 2 Sample T-test The 2 sample t-test shows that the estimated difference between means is -794.9. The P value is 0.0457 which is lower than 0.05 that is why we reject the Null hypothesis and follow the Alternative one. There is not enough evidence to conclude that the difference between the population means is statistically significant. So with a 95 percent confidence interval we can assume that the mean is between -1574.3 and -15.5 If we analysis all the above given facts and figures we should be very clear in our minds that is the advertisement source can be of many types, but as we compare here two radios and newspapers in that case newspapers get better in this case and suggested to the body shock company to expend its expenditures on newspapers for the advertisement. In which they can focus on different scenarios like prices and giving facilities etc. The values given by the statistical analysis by taking 45 samples, maximum value of the radio is about 11 thousand, whereas the maximum value of the news is about 12 thousand which is higher value than that. Means the newspaper is best for advertisement for the company rather than radio for this purpose. PART 2: According to data given, rise and fall in histogram statistics are proceeding in the same manner for both advertising mediums. However, this rise, rise in magnitude is more for news in comparison with radio as shown in statistical figure below. To imitate the future cost and current expenditure of company on these two mediums the correlation among data is analyzed whose result is mentioned below. Since the results show that correlation coefficients are all equal to 1 means that there is a strong correlation between the two variable. Increase and decrease in both medium expenditure is similar so in order to further increase the impact of an advertisement, company may cut down some of its expenditure from radio and expend more on the news because the news is giving a better opportunity to enhance its awareness. Moreover, the best line fit model is used to analyze the way of effective advertisement based on expense company is making on these two. The result of the line fitting model also shows that news is the best option for reducing company expense on marketing. As the cost of each advertisement are almost similar but the effect is much more visible for news. Line model is nearer to many point of news (red circles in line model figure) hence it is suggested to cut down some the expense from radio communication. This will be beneficial for the company’s economic as well as for people getting information from paper and news resources. Another statistic using regression model is carried out for both news and radio advertisement. Results show that their upper and lower bounds for both are near around each other since they have similar trends of cost. Also the values in the stats result of regression show that estimated error is small when news is considered as predictor in regression. Also, as stated in part above the P value is 0.0457 for an advert which is lower than 0.05. And the values of p which is less than 0.05 are suggested to use alternative value instead of null hypothesis, therefore here the null hypothesis is rejected and alternative hypothesis will be preferred. Considering all figures and results it is suggested to use the news as a much appropriate medium of advertisement. The reduction in cost of radio will give economic strength to the company and also the enhanced way of advertising on the news will give smooth communication and awareness among people. Future spending of the company must rely mostly on news and thereby currents expense stats must be changed. References: 1: William M.K. Trochim, 2006, Research Methods: Knowledge base, Web center for social research methods,” http://www.socialresearchmethods.net/kb/statdesc.php”,last Revised: 10/20/2006 2: Valerie J. Easton & John H McColl’s 98, Statistics, V1.1. http://www.stat.yale.edu/Courses/1997-98/101/boxplot.htm Read More