In the context of estimating a population parameter, how does decreasing the confidence level affect the sample size required to achieve a fixed margin of error?
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 29m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
4. Probability
Basic Concepts of Probability
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Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
Suppose has a uniform distribution on the interval . What is the probability that ?
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Verified step by step guidance1
Recognize that the random variable \(x\) follows a uniform distribution on the interval \([0, 1]\). This means that the probability density function (pdf) is constant over this interval.
Recall that for a uniform distribution on \([a, b]\), the pdf is given by \(f(x) = \frac{1}{b - a}\) for \(a \leq x \leq b\). Here, \(a = 0\) and \(b = 1\), so \(f(x) = 1\) for \$0 \leq x \leq 1$.
The probability that \(x\) is less than a certain value \(c\) within the interval \([0, 1]\) is the area under the pdf from \(a\) to \(c\). Mathematically, this is \(P(x < c) = \int_a^c f(x) \, dx\).
Substitute the values into the integral: \(P(x < 0.25) = \int_0^{0.25} 1 \, dx\).
Evaluate the integral to find the probability: \(P(x < 0.25) = 0.25 - 0 = 0.25\). This is the probability that \(x\) is less than 0.25.
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