Interval estimation definitions
| Word backwards | lavretni noitamitse |
|---|---|
| Part of speech | Interval estimation is a noun phrase. |
| Syllabic division | in-ter-val es-ti-ma-tion |
| Plural | The plural of the word interval estimation is interval estimations. |
| Total letters | 18 |
| Vogais (4) | i,e,a,o |
| Consonants (7) | n,t,r,v,l,s,m |
Interval estimation is a statistical method used to estimate an unknown population parameter by constructing a range of values that is likely to contain the true value. This range is called a confidence interval, and it provides a measure of the uncertainty associated with the estimation process.
How Interval Estimation Works
In interval estimation, a sample from the population is used to calculate a point estimate of the parameter of interest, such as the population mean or proportion. This point estimate is then used to determine the boundaries of the confidence interval, which takes into account the variability of the sample data and the desired level of confidence.
Confidence Level and Confidence Interval
The confidence level is the probability that the true parameter value lies within the confidence interval. Common confidence levels include 90%, 95%, and 99%. A higher confidence level results in a wider confidence interval, reflecting a greater degree of certainty in the estimation.
Factors Affecting Interval Estimation
Several factors can affect the width of a confidence interval, including the sample size, the variability of the data, and the chosen confidence level. A larger sample size will typically result in a narrower confidence interval, while higher variability or lower confidence levels will widen the interval.
Interval estimation is commonly used in hypothesis testing, where researchers compare the confidence interval of a parameter to a hypothesized value. If the hypothesized value lies outside the confidence interval, it suggests that there is sufficient evidence to reject the null hypothesis in favor of an alternative hypothesis.
Conclusion
Interval estimation provides a valuable tool for researchers and decision-makers to make informed inferences about population parameters based on sample data. By considering the variability of the data and the desired level of confidence, interval estimation allows for a more nuanced understanding of the uncertainty inherent in statistical estimation.
Interval estimation Examples
- Researchers used interval estimation to determine the average height of a certain plant species.
- The marketing team relied on interval estimation to forecast sales for the upcoming quarter.
- Scientists utilized interval estimation to estimate the lifespan of a newly discovered species of fish.
- Statisticians employed interval estimation to calculate the margin of error in a survey.
- Economists used interval estimation to predict the growth rate of the stock market.
- Health professionals applied interval estimation to assess the effectiveness of a new medication.
- Social scientists employed interval estimation to analyze the income distribution among different demographics.
- Engineers utilized interval estimation to determine the reliability of a new technology.
- Educators relied on interval estimation to evaluate the impact of a teaching intervention on student performance.
- Policy makers used interval estimation to estimate the number of people living below the poverty line.