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  1. Statistical multiplexing refers to the phenomenon whereby sources with statistically varying rates are mixed or input into a common server or buffer. Typical sources that occur are ”bursty”- there

  2. Analyze the problem: think carefully about the null and alternative hypotheses. Choose a test statistic. Calculate the test statistic for the original labeling of the observations. Permute the labels and recalculate the test statistic. Do all permutations: Exact Test.

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  3. Hypothesis Testing – Examples and Case Studies. 23.1 How Hypothesis Tests Are Reported in the News. Determine the null hypothesis and the alternative hypothesis. Collect and summarize the data into a . test statistic. Use the test statistic to determine the p-value. The result is statistically significant if the .

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  4. Statistical hypothesis testing –Helps us decide if a sample belongs to a population • A priori calculation of important statistical properties can help design better studies –Power, sample size, effect size

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  5. Paired-samples t-test. If we consider each data point to be independent, then we find no significance (p = .491), because the between-group variance is small relative to the within-group variance. A paired-samples t-test accounts for differences between individuals, revealing the effect of condition on each (p < .001)

  6. Jan 28, 2020 · Statistical tests work by calculating a test statistic – a number that describes how much the relationship between variables in your test differs from the null hypothesis of no relationship. It then calculates a p value (probability value).

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  8. Introduction to Hypothesis Testing. LEARNING OBJECTIVES. After reading this chapter, you should be able to: CHAPTER 8. 8.1 Inferential Statistics and Hypothesis Testing. 8.2 Four Steps to Hypothesis Testing. 8.3 Hypothesis Testing and Sampling Distributions. 8.4 Making a Decision: Types of Error.

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