About This Chapter
Cambridge Pre-U Math Short Course: Statistical Estimation - Chapter Summary
Explore this chapter on statistical estimation as you prepare for the Cambridge Pre-U Math Short Course test. Video lessons and quizzes can guide you in understanding and solving formulas related to point and interval estimations, confidence intervals, estimators and proportions. You'll also find several examples that could improve your capacity to:
- Compare interval and point estimations
- Calculate sample size and confidence intervals
- Provide examples of the use of t distribution
- Solve problems involving t distribution
- Distinguish between biased and unbiased estimators
- Work with confidence intervals for proportions
- Calculate confidence intervals from independent samples with equal and unequal variances or different proportions
Designed and delivered by professional educators, the lessons can increase your knowledge of statistical estimation through quizzes, videos, transcripts and links to related courses. Request additional help by visiting the Dashboard and asking the experts about statistical estimation concepts.
Cambridge Pre-U Math Short Course: Statistical Estimation Chapter Objectives
Made up of two components, the written Cambridge Pre-U Math Short Course examination will test your understanding of statistical estimation and allow you to utilize the knowledge you gained throughout this chapter. Paper 1 and Paper 2 of the test are also known as Pure Mathematics and Statistics, respectively. Pure Mathematics will take up to one hour and 45 minutes to complete. With 65 questions, it measures 45% of the test weighting. The Statistics component contains 80 questions that must be answered within two hours of the starting time. It's worth 55% of the test weighting. Enjoy the flexibility and convenience of studying these online lessons as you get ready to answer Cambridge Pre-U Math Short Course assessment questions.
1. Point & Interval Estimations: Definition & Differences
Statisticians have to use estimation to describe and infer information from gathered data. In this lesson, you will learn about the two types of estimation used: point and interval estimation.
2. Calculating Confidence Intervals, Levels & Coefficients
In this lesson, you're going to learn about confidence intervals, confidence levels, and coefficients, and how they relate to point estimates and interval estimates.
3. Finding Confidence Intervals with the Normal Distribution
In this lesson, you're going to learn how to construct a confidence interval when the population's standard deviation is known and the population is normally distributed.
4. Determining the Sample Size to Estimate Confidence Intervals: Definition & Process
In this lesson, you will learn how to determine the most appropriate sample size to find the confidence interval we need using a specific case example.
5. Student t Distribution: Definition & Example
In this lesson, you're going to learn about the t-distribution, t-curves, their important properties, and differences from the standard normal distribution as well as how to find the value of t.
6. Using the t Distribution to Find Confidence Intervals
In this lesson, you're going to learn how we find confidence intervals for normally distributed populations where the population standard deviation is not known. Work through the sample, then test your understanding with a brief quiz.
7. Biased & Unbiased Estimators: Definition & Differences
When dealing with statistics, you've probably heard about why it is wise to avoid biased estimators. However, as this lesson proves, sometimes a biased estimator can be pretty useful—if you know how to use it.
8. Finding Confidence Intervals for Proportions: Formula & Example
In this lesson, you're going learn how to figure out the margin of error, confidence interval, and point estimate for a population proportion with large sample sizes.
9. Confidence Intervals: Mean Difference from Two Independent Samples
Learn how to find a probable range for the difference in means between two independent samples of data. Build a confidence interval using sample means, sample sizes, sample standard deviations, and t-tables.
10. Confidence Intervals: Mean Difference from Two Independent Samples & Equal Variance
In this lesson, we derive a formula for a confidence interval for the difference of two population means. The samples are assumed to be independent and taken from two normal distributions with possibly different means and equal standard deviations. In addition, the common standard deviation is assumed to be unknown.
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Other chapters within the Cambridge Pre-U Mathematics - Short Course: Practice & Study Guide course
- Cambridge Pre-U Math Short Course: Quadratic Equations
- Cambridge Pre-U Math Short Course: Coordinate Geometry
- Cambridge Pre-U Math Short Course: Sequences & Series
- Cambridge Pre-U Math Short Course: Exponentials & Logarithms
- Cambridge Pre-U Math Short Course: Differentiation
- Cambridge Pre-U Math Short Course: Integration
- Cambridge Pre-U Math Short Course: Data Summarization
- Cambridge Pre-U Math Short Course: Correlation & Regression
- Cambridge Pre-U Math Short Course: Binomial Distribution
- Cambridge Pre-U Math Short Course: Normal Distribution
- Cambridge Pre-U Math Short Course: Sampling
- Cambridge Pre-U Math Short Course: Hypothesis Testing
- Cambridge Pre-U Math Short Course: Chi-Square Test
- Cambridge Pre-U Math Short Course: Non-Parametric Tests
- Cambridge Pre-U Mathematics - Short Course Flashcards