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CNLS 503 Module 4 2026 – Complete Exam Study Guide and Practice Questions with Answers

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This document covers the key statistical concepts from CNLS 503 Module 4, including the normal distribution, z-scores, hypothesis testing, confidence intervals, effect size, and statistical power. It is presented in a question-and-answer format, making it useful for exam preparation and quick review of essential formulas, definitions, and critical values. The material also includes one-tailed and two-tailed hypothesis testing, APA reporting, and Cohen’s d guidelines. It serves as a concise study guide for students preparing for Module 4 assessments. Keywords Normal distribution Z-score Standard score Raw score Hypothesis testing Null hypothesis Alternative hypothesis One-tailed test Two-tailed test Critical values Confidence interval Statistical power Effect size Cohen's d Standard deviation Sample mean Standard normal table APA reporting Exam questions Statistics review

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CNLS 503 Mod 4 2026 Expert
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normal distribution - ANSWER ✔✔a frequency distribution that is

shaped like a symmetrical bell, unimodal curve


total relative frequency of distribution - ANSWER ✔✔area under

curve = 100% of the data or 1.0


68% of values - ANSWER ✔✔% fall within 1 standard deviation of

mean


95% of values - ANSWER ✔✔% fall within 2 standard deviations of

mean

, 99.7 % of values - ANSWER ✔✔fall with in 3 standard deviations of

he mean


normal curve defined by - ANSWER ✔✔mean and standard deviation


raw score - ANSWER ✔✔exact value that is observed


standard score - ANSWER ✔✔indicates exactly how many standard

deviations a raw score is above or below the mean. Z-score


What is the purpose of calculating z-scores? - ANSWER ✔✔The

purpose of calculating z-scores is to understand a score's relative

standing within a distribution. The z-score standardizes scores from

different data sets with different means


formula for raw score to z-score - ANSWER ✔✔


formula for z-score to raw score - ANSWER ✔✔


formula for sample mean to z-score - ANSWER ✔✔divided by

standard error o/square root of sample


standard normal table - ANSWER ✔✔Shows the proportion of values

that fall to the left (or below) of a given z-score in a normal distribution


How to find percentage above z-score - ANSWER ✔✔1- p-value

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