materi presentasi statistika bisnis pert 2

materi statbis

1. Ethics and Statistics a) Following events such as Wall Street money manager Bernie Madoff’s Ponzi scheme, which swindled billions from investors, and financial misrepresentations by Enron and Tyco, business students need to understand that these events were based on the misrepresentation of business and financial data. b) In each case, people within each organization reported financial information to investors that indicated the companies were performing much better than the actual situation. c) When the true financial information was reported, the companies were worth much less than advertised. The result was many investors lost all or nearly all of the money they put into these companies.

2. FREQUENCY TABLE A grouping of qualitative data into mutually exclusive classes showing the number of observations in each class. Graphic Presentation of Qualitative Data

3. BAR CHART A graph that shows qualitative classes on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are proportional to the heights of the bars. Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation 2

4. PIE CHART A chart that shows the proportion or percentage that each class represents of the total number of frequencies .

5. 2.3 Constructing Frequency Distributions: Quantitative Data Step 1: Decide on the number of classes. Step 2: Determine the class interval or class width. Generally the class interval or class width is the same for all classes Step 3: Set the individual class limits. Step 4: Tally the vehicle profit into the classes . Step 5: Count the number of items in each class. TABLE 2–7 Frequency Distribution of Profit for Vehicles Sold Last Month at Applewood Auto Group

6. Frequency Polygon A frequency polygon also shows the shape of a distribution and is similar to a his togram . It consists of line segments connecting the points formed by the intersections of the class midpoints and the class frequencies.

7. The total number of cars sold at the two dealerships is about the same, so a direct comparison is possible. If the difference in the total number of cars sold is large, then converting the frequencies to relative frequencies and then plotting the two distributions would allow a clearer comparison.

8. Cumulative Frequency Distributions

9. 3.9 The Relative Positions of the Mean, Median, and Mode

10. Describing Data: Numerical Measures

11. 3.4 Properties of the Arithmetic Mean  IPK 1. Every set of interval- or ratio-level data has a mean. 2. All the values are included in computing the mean. 3. The mean is unique. That is, there is only one mean in a set of data. 4. The sum of the deviations of each value from the mean is zero.

12. 3.6 The Median We have stressed that, for data containing one or two very large or very small values, the arithmetic mean may not be representative. The center for such data can be better described by a measure of location called the median . The median can be determined for all levels of data but the nominal . It is not affected by extremely large or small values. It can be computed for ordinal-level data or higher. Median  Quartile  Decile  Percentile .

13. A second application of the geometric mean is to find an average percentage change over a period of time. For example, if you earned $30,000 in 2000 and $50,000 in 2010, what is your annual rate of increase over the period? It is 5.24 percent. The rate of increase is determined from the following formula.

14. 3.11 Why Study Dispersion? A measure of dispersion can be used to evaluate the reliability of two or more measures of location

15. 3.12 Measures of Dispersion Range is The simplest measure of dispersion is the range. The range is widely used in statistical process control (SPC) applications because it is very easy to calculate and understand. Mean Deviation A defect of the range is that it is based on only two values, the highest and the lowest; it does not take into consideration all of the values.

16. 3.10 The Geometric Mean The geometric mean is useful in finding the average change of percentages, ratios, indexes, or growth rates over time. It has a wide application in business and economics because we are often interested in finding the percentage changes in sales, salaries, or economic figures, such as the Gross Domestic Product, which compound or build on each other. As an example of the geometric mean , suppose you receive a 5 percent increase in salary this year and a 15 percent increase next year. The average annual percent increase is 9.886, not 10.0 The return on investment earned by Atkins Construction Company for four successive years was: 30 percent, 20 percent, - 40 percent, and 200 percent. What is the geometric mean rate of return on investment?

17. Variance and Standard Deviation The variance and standard deviation are also based on the deviations from the mean. However, instead of using the absolute value of the deviations, the variance and the standard deviation square the deviations .

18. 3.15 The Mean and Standard Deviation of Grouped Data

19. Stem-and-Leaf Displays There are two disadvantages, however, to organizing the data into a frequency distribution: (1) we lose the exact identity of each value and (2) we are not sure how the values within each class are distributed. An advantage of the stem-and-leaf display over a frequency distribution is that we do not lose the identity of each observation. A stem-and-leaf display is similar to a frequency distribution with more information, that is, the identity of the observations is preserved. We can also generate this information on the Minitab software system. We have named the variable Spots.

20. 4.4 Measures of Position Quartiles, Deciles, and Percentiles