Applied Statistics for Business and Economics by Robert M. Leekley

By Robert M. Leekley

Designed for a one-semester path, Applied records for company and Economics bargains scholars in enterprise and the social sciences a good advent to a few of the main uncomplicated and strong innovations to be had for figuring out their international. a variety of attention-grabbing and demanding examples replicate real-life events, stimulating scholars to imagine realistically in tackling those difficulties. Calculations might be played utilizing any typical spreadsheet package deal. to assist with the examples, the writer deals either genuine and hypothetical databases on his site http://iwu.edu/~bleekley

The textual content explores how one can describe information and the relationships present in information. It covers easy chance instruments, Bayes’ theorem, sampling, estimation, and self belief durations. The textual content additionally discusses speculation trying out for one and samples, contingency tables, goodness-of-fit, research of variance, and inhabitants variances. moreover, the writer develops the recommendations at the back of the linear courting among numeric variables (simple regression) in addition to the doubtless nonlinear relationships between greater than variables (multiple regression). the ultimate bankruptcy introduces classical time-series research and the way it applies to company and economics.

This textual content offers a realistic figuring out of the price of facts within the actual global. After analyzing the ebook, scholars might be capable of summarize info in insightful methods utilizing charts, graphs, and precis information in addition to make inferences from samples, specially approximately relationships.

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Example text

2 Histograms A histogram is essentially a bar chart for continuous numeric data. In the bar chart by Major, large gaps between bars communicate the fact that these majors are distinct. If you were to make a bar chart for discrete numeric data, you would want that as well. With continuous data, though, the groupings are artificial. The values stretch over a range, with the largest value in one grouping being not very different from the smallest number in the next grouping. That fact is indicated by running the bars together.

Sometimes your only real interest is to describe what a given set of data looks like. You want to inform your intuition or perhaps someone else’s. How big are the numbers? How spread out are they? Are they skewed one way or the other? If this describes your goal, frequency distributions, tables, and graphs are excellent tools. 3 was an example of how one might use a graph to do so. 2 made good use of graphs as well. Chapter 2 will be, devoted to describing data in such ways. Of course, usually, if you are trying to describe something, it is because you think it is worth describing.

However, suppose you want to emphasize the relative sizes of these frequencies. In that case, a pie chart might be more effective. It emphasizes how much each frequency is of the whole. It also allows you to highlight a particular group, by “exploding” its slice, if there is a group to which you would like to draw attention. 9 with just a few clicks of a mouse. 8 Bar chart of the distribution of students by major. 2 Histograms A histogram is essentially a bar chart for continuous numeric data. In the bar chart by Major, large gaps between bars communicate the fact that these majors are distinct.

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