What Is An Interval Estimate Of A Population Parameter?

by | Last updated on January 24, 2024

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Interval estimation, in statistics,

the evaluation of a parameter

—for example, the mean (average)—of a population by computing an interval, or range of values, within which the parameter is most likely to be located.

What is interval estimation with example?

An interval is

a range of values for a statistic

. For example, you might think that the mean of a data set falls somewhere between 10 and 100 (10 < μ < 100). A related term is a point estimate, which is an exact value, like μ = 55. … That “somewhere between 5 and 15%” is an interval estimate.

What is an interval estimate of a population mean?

An interval estimate is defined

by two numbers, between which a population parameter is said to lie

. For example, a < x < b is an interval estimate of the population mean μ. It indicates that the population mean is greater than a but less than b.

What is an interval estimate for an unknown population parameter?

An interval estimate for an unknown population parameter. This depends on: …

The percent expression for the probability that the confidence interval contains the true population parameter

; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter.

Why is the interval estimate preferred value for the population parameter?

Interval estimation is the range of numbers in which a population parameter

lies considering margin of error

. Because there is a certain level of uncertainty, an interval estimate gives a range, rather than a single value, of the population parameters.

How do you calculate the interval estimate of a population?

When the population standard deviation is known, the formula for a confidence interval (CI) for a population mean is

x̄ ± z* σ/√n

, where x̄ is the sample mean, σ is the population standard deviation, n is the sample size, and z* represents the appropriate z*-value from the standard normal distribution for your desired …

What is meant by interval estimate?

Interval estimation, in statistics,

the evaluation of a parameter

—for example, the mean (average)—of a population by computing an interval, or range of values, within which the parameter is most likely to be located.

What is interval estimate formula?

Suppose we want to generate a 95% confidence interval estimate for an unknown population mean. This means that there is a 95% probability that the confidence interval will contain the true population mean. Thus,

P( [sample mean] – margin of error < μ < [sample mean] + margin of error)

= 0.95.

How do you calculate intervals?

  1. α : subtract the given CI from 1. 1-.9=.10.
  2. z

    α / 2

    : divide α by 2, then look up that area in the z-table. …
  3. : Divide the proportion given (i.e. the smaller number)by the sample size. …
  4. : To find q-hat, subtract p-hat (from directly above) from 1.

What is interval data example?

Interval data is measured on an interval scale. A simple example of interval data:

The difference between 100 degrees Fahrenheit and 90 degrees Fahrenheit is the same as 60 degrees Fahrenheit and 70 degrees Fahrenheit.

What is the difference between a point estimate and an interval estimate?

A point estimate is a

single value estimate of a parameter

. … For instance, a sample mean is a point estimate of a population mean. An interval estimate gives you a range of values where the parameter is expected to lie.

Where should a confidence interval be centered?

A confidence interval, centered

on the mean of your sample

, is the range of values that is expected to capture the population mean with a given level of confidence. A wider confidence interval is a greater range of values, resulting in a greater confidence level that the range will include the population mean.

What are the two types of estimation?

There are two types of estimates:

point and interval

. A point estimate is a value of a sample statistic that is used as a single estimate of a population parameter.

Why is an interval estimate better than a point estimate?

An interval estimate (i.e., confidence intervals) also

helps one to not be so confident that the population value is exactly equal to the single point estimate

. That is, it makes us more careful in how we interpret our data and helps keep us in proper perspective.

How do you know if a confidence interval is successful?

So, if your significance level is 0.05, the corresponding confidence level is 95%. If the P value is less than your significance (alpha) level, the hypothesis test is statistically significant. If the confidence interval does not contain the null hypothesis value, the results are

statistically

significant.

When a range of values is used to estimate a population parameter?


interval estimate

: A range of values used to estimate a population parameter.

Kim Nguyen
Author
Kim Nguyen
Kim Nguyen is a fitness expert and personal trainer with over 15 years of experience in the industry. She is a certified strength and conditioning specialist and has trained a variety of clients, from professional athletes to everyday fitness enthusiasts. Kim is passionate about helping people achieve their fitness goals and promoting a healthy, active lifestyle.