Data Analysis

Presenting Qualitative Data: & tinkers damn;BAR CHARTS •PIE CHARTS Presenting quantitative Data: •FRQUENCY TABLES Age of CEOs in South easternmost Queensland: 4567375167 5051504749 3539525955 6070556440 4946485742 Frequency distribution of ages of CEOs: Approximate act of classes in a frequency distribution Number of observationsNumber of classes slight than 505 to 7 50 - 207 to 9 cc - 5009 to 10 500 – 1,00010 or 11 1,000 – 5,00011 to 13 5,000 – 50,00013 to 17 More than 50,00017 to 20 •HISTOGRAMS • moving in GRAPHS (TIME SERIES DATA) For example quarterly gross sales figures: • pick PLOTS (BIVARIATE DATA) Good for both time-series & cross-sectional data. exalted for: o deed control oExamining sexual intercourseships among two variables There appears to be a negative and fairly blotto linear relation between age and days absent. •Box-plots • diss eminate plots moment Level and Rejection Region The real question is how strong the evidence in favor of the alternative surmisal essential be to pass the null hypothesis.

The analyst holds the probability of a type I error that he is willing to tolerate. The appreciate is denoted by a and is most commonly equal to 0.05, although a =0.01 and a =0.10 are also frequently intentd. The value of a is called the significance take of the test. Then, given the value of a, we use statistical theory to determine the pooh-poohion region. If the sample waterfall into this region we reject the nul l hypothesis; otherwise, we do not reject it! .  experiment evidence that falls into the rejection region is called statistically significant at the a take. consequence from p-values This approach is currently more hot than the significance level and rejection region approach. This approach is to avoid the use of the a level and instead...If you want to get a encompassing essay, order it on our website: BestEssayCheap.com

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