(the alpha level), a probability level (alpha level), used as a cut off point at which you would consider a result to very unlikely. For example, we could calculate the mean and standard deviation of the exam marks for the 100 students and this could provide valuable information about this group of 100 students. Inferential statistics are techniques that allow us to use these samples to make generalizations about the populations from which the samples were drawn. Descriptive statistics: As the name implies, descriptive statistics focus on providing you with a description that illuminates some characteristic of your numerical dataset. Inferential statistics use samples to draw inferences about larger populations. there is statisically significant difference between the means of the two conditions, two groups of subject, independent from eachother, one group of subject (pre/post) or (crossover design). A sample of the data is considered, studied, and analyzed. Criteria for using each of Inferential Statistical Tests. Consider how descriptive statistics and inferential statistics can both apply to the many roles tied to accounting, as well as the important differences between them. a t-test which is generalized to more than 2 groups, WORKS for more than two groups, differences between the mean of the group/conditions. Estimation = estimating about the population parameters based on the statistics from the randomly selected sample. It focuses on drawing … Inferential statistics, unlike descriptive statistics, is the attempt to apply the conclusions that have been obtained from one experimental study to more general populations. chance), The means of the population, from which the samples are drawn, are EQUAL. The examples regarding the 100 test scores was an analysis of a population. Meaning of inferential statistics. BP measured once a week for three months, more than one dependent variable (when DV's are highly correlated). We have seen that descriptive statistics provide information about our immediate group of data. The average salary of the graduates of the class of 1980 is $32,500. Reject the null hypothesis, the results are statistically significant. Next What Are Statistics. Inferential statistics is the most critical branch of Statistics that mainly uses sample data drawn from a given population. The method used is tested mathematically and can be regarded as an unbiased estimator. Descriptive & Inferential Statistics. Inferential Statistics. Knowledge Base written by Prof William M.K. I recommend using the book after you have seen the movies. What is a research hypothesis simplified? Descriptive Statistics collects, organises, analyzes and presents data in a meaningful way. Learn inferential statistics with free interactive flashcards. Inferential Statistics In a nutshell, inferential statistics uses a small sample of data to draw inferences about the larger population that the sample came from. Inferential statistical tests are more powerful than the descriptive statistical tests like measures of central tendency (mean, mode, median) or measures of dispersion (range, standard deviation). Great! Check out the learning objectives, start watching the videos, and finally work on the quiz and the labs of this week. We use inferential statistics to try to infer from the sample data what the population might think. Let’s take a glance at … Slide 10: Inferential statistics use information about a sample (a group within a population) to tell a story about a population. what you do with your data. decision making process to estimate population characteristics from sample data. The module explains the importance of random sampling to avoid bias. Q. Classify the following as descriptive or inferential statistics. Inferential Statistics: Statistics are divided into two major categories: descriptive and inferential. 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