STATISTICS

Statistics

Statistics

The article compares the relative growth in sales and profits of U.S. companies listed restaurant over a period of 20 years from 1981 to 2000. Although no significant differences in sales growth among domestic and international restaurants. However, multinational companies are much better than domestic firms in increasing operating margins and earnings before taxes. Multinational companies also had significantly lower negative growth of domestic pre-tax in comparison to local companies. Traditionally, many restaurants, businesses tend to initially focus on regional development. This is reasonable based on customers' tastes and preferences of similar logistics of distribution and possible economies of scale (Singh, Upneja & Dalbor, 2003). Eventually, however, international expansion seems to be the right strategy. As in the case of McDonald, the bulk of its new offshore development (Lombardi, 1996). This is not only because of possible saturation of the local U.S. market, but also a higher operating margin earned by multinational companies. Given the relatively low margins of operations of the many restaurants, any increase in operating margins have a great influence on the result.

The statistical technique which is used to compare the domestic and international restaurants is t-test analysis. The t-test is the most commonly used method for detecting differences between the average of two samples. For example, t-test can be used to compare the average of the group of patients taking certain medications, with the control group, which was taken placebo. Theoretically, t-test can be applied even if the sample sizes are very small (for example some researchers argue that it is possible to investigate samples of smaller size), and if the variables are normally distributed (in groups), and the dispersion of observations in the groups are not too different. When using T-test we are to identify the significant differences between the averages of two groups is not only, but if the goal is to identify the significant differences between the averages of more than two groups to talk about this case is a one-way analysis of variance.

The implications of t-test

The number of elements of the series - the sample size used in this procedure

Average - the average number of elements

The standard error (mean) - describes the standard deviation of the sample mean

The level of significance

The value of T-test - test the value of t.

P (T <= t) (probability corresponding to the Student's criterion) - p-level of significance t-test is the probability of falsely rejecting the hypothesis of equality of means of two samples, when in fact this hypothesis is valid. In other words, it is equal to the error probability to the hypothesis that inequality of means, when in fact means the same.

One of the most common statistical problems is to test hypotheses about the expectation of the investigated samples. There are a number of statistical tests, called the Student's t-tests that test different hypotheses about expectation. This test is used to test the hypothesis that the expectation of a random variable X, provided a sample of x S, has a given value of ...