The data set consists of the numbers 1 up through , with each value occurring once. The histogram will be uniform. All three histograms are somewhat mound-shaped with the top of the mound between 9. In all three histograms the bulk of the data fall between 8 and No, each random sample of same size froma population is equally likely to be drawn. Sample iii most clearly reflects the properties of the population. Sample ii reflects the properties fairly well, but sample i seems to differ more from the described population.
Because there are 50 data values, divide each cumulative frequency by 50 and convert to a percent. To create the ogive, place a dot on the x axis at the lower class boundary of the first class, and then, for each class, place a dot above the upper class boundary value at the height of the cumulative frequency for the class. Connect the dots with line segments. The dotplot shows some of the characteristics of the histogram, such as the concentration of most of the data in two peaks, one from 13 to 24 and another from 37 to Measures of Variation.
Percentiles and Box-and-Whisker Plots. Scatter Diagrams and Linear Correlation. Linear Regression and the Coefficient of Determination. What is Probability? Some Probability Rules-Compound Events. Trees and Counting Techniques. Introduction to Random Variables and Probability Distributions. Binomial Probabilities. Additional Properties of the Binomial Distribution. Graphs and Normal Probability Distributions. Areas Under Any Normal Curve. Sampling Distributions. The Central Limit Theorem. Estimating When s Is Known.
Estimating When s is Unknown. Estimating p in a Binomial Distribution. Introduction to Statistical Tests. Testing the Mean. Testing a Proportion p. Inferences About the Difference of Two Means 1 - 2. Inferences About the Difference of Two Proportions p1 - p2. Chi-Square: Tests of Independence and of Homogeneity. Chi-Square: Goodness of Fit. Inferences for Correlation and Regression. Convert currency.
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