**Asked by:**Garrett Emard

**Updated:**4 November 2021 12:04:00 PM

# In a normal distribution what percent of the values lie?

In normally distributed data, about 34% of the values lie between the mean and one standard deviation below the mean, and 34% between the mean and one standard deviation above the mean. In addition, 13.5% of the values lie between the first and second standard deviations above the mean.

## Taking this into account what percentage of the data in a normal distribution?

In any normal distribution with mean μ and standard deviation σ : Approximately 68% of the data fall within one standard deviation of the mean. Approximately 95% of the data fall within two standard deviations of the mean. Approximately 99.7% of the data fall within three standard deviations of the mean.## Accordingly, the question is what percentage of the normal distribution lies between and +1z?

About 68% of the values lie between the values 41 and 63. About 95% of the values lie between the values 30 and 74. About 99.7% of the values lie between the values 19 and 85.## In addition what does a normal distribution tell us?

It is a statistic that tells you how closely all of the examples are gathered around the mean in a data set. The shape of a normal distribution is determined by the mean and the standard deviation. The steeper the bell curve, the smaller the standard deviation.## Do you have your own answer or clarification?

### Related questions and answers

#### What is the five properties of normal distribution?

Properties of a normal distribution The mean, mode and median are all equal. The curve is symmetric at the center (i.e. around the mean, μ). Exactly half of the values are to the left of center and exactly half the values are to the right. The total area under the curve is 1.

#### What are the 4 properties of normal distribution?

Characteristics of Normal Distribution Here, we see the four characteristics of a normal distribution. Normal distributions are symmetric, unimodal, and asymptotic, and the mean, median, and mode are all equal. A normal distribution is perfectly symmetrical around its center.

#### When should we not use normal distribution?

Insufficient Data can cause a normal distribution to look completely scattered. For example, classroom test results are usually normally distributed. An extreme example: if you choose three random students and plot the results on a graph, you won't get a normal distribution.

#### What percent of values are below 81?

2.5% f) What percent of values are below 81? 16% 6. Given an approximately normal distribution with a mean of 159 and a standard deviation of 70.

#### What interval contains 68 of all values?

About 68% of values fall within one standard deviation of the mean. About 95% of the values fall within two standard deviations from the mean. Almost all of the values - about 99.7% - fall within three standard deviations from the mean.

#### What are the five properties of normal distribution?

The shape of the distribution changes as the parameter values change.

- Mean. The mean is used by researchers as a measure of central tendency.
- Standard Deviation.
- It is symmetric.
- The mean, median, and mode are equal.
- Empirical rule.
- Skewness and kurtosis.

#### What are the 5 properties of a normal distribution?

The shape of the distribution changes as the parameter values change.

- Mean. The mean is used by researchers as a measure of central tendency.
- Standard Deviation.
- It is symmetric.
- The mean, median, and mode are equal.
- Empirical rule.
- Skewness and kurtosis.

#### What is a good 95% confidence interval?

A 95% confidence interval was computed of [0.410, 0.559]. The correct interpretation of this confidence interval is that we are 95% confident that the correlation between height and weight in the population of all World Campus students is between 0.410 and 0.559.

#### What does a 95% confidence interval tell you?

The 95% confidence interval is a range of values that you can be 95% confident contains the true mean of the population. For example, the probability of the population mean value being between -1.96 and +1.96 standard deviations (z-scores) from the sample mean is 95%.

#### What are the important properties of a normal distribution?

Properties of a normal distribution The mean, mode and median are all equal. The curve is symmetric at the center (i.e. around the mean, μ). Exactly half of the values are to the left of center and exactly half the values are to the right. The total area under the curve is 1.

#### What interval contains 95% of all values?

The 95% confidence interval defines a range of values that you can be 95% certain contains the population mean. With large samples, you know that mean with much more precision than you do with a small sample, so the confidence interval is quite narrow when computed from a large sample.

#### What are the four properties of a normal distribution?

Characteristics of Normal Distribution Here, we see the four characteristics of a normal distribution. Normal distributions are symmetric, unimodal, and asymptotic, and the mean, median, and mode are all equal. A normal distribution is perfectly symmetrical around its center.

#### What are the characteristics of a normal distribution?

Properties of a normal distribution

- The mean, mode and median are all equal.
- The curve is symmetric at the center (i.e. around the mean, μ).
- Exactly half of the values are to the left of center and exactly half the values are to the right.
- The total area under the curve is 1.

#### How do you interpret a normal distribution curve?

The area under the normal distribution curve represents probability and the total area under the curve sums to one. Most of the continuous data values in a normal distribution tend to cluster around the mean, and the further a value is from the mean, the less likely it is to occur.

#### What percent of values lie below the mean?

In normally distributed data, about 34% of the values lie between the mean and one standard deviation below the mean, and 34% between the mean and one standard deviation above the mean. In addition, 13.5% of the values lie between the first and second standard deviations above the mean.

#### What are the disadvantages of normal distribution?

One of the disadvantages of using the normal distribution for reliability calculations is the fact that the normal distribution starts at negative infinity. This can result in negative values for some of the results. For example, the Quick Calculation Pad will return a null value (zero) if the result is negative.

#### What is the 95 rule in statistics?

In statistics, the empirical rule states that 99.7% of data occurs within three standard deviations of the mean within a normal distribution. To this end, 68% of the observed data will occur within the first standard deviation, 95% will take place in the second deviation, and 97.5% within the third standard deviation.

#### What does 95% confidence mean in a 95% confidence interval?

Strictly speaking a 95% confidence interval means that if we were to take 100 different samples and compute a 95% confidence interval for each sample, then approximately 95 of the 100 confidence intervals will contain the true mean value (μ).

#### What are the 5 properties of normal distribution?

#### What are the advantages of normal distribution?

Probability Density Function, PDF One of the advantages of the normal distribution is due to the central limit theorem. The averages of a sample from a slightly skewed distribution, will be normally distributed.

#### What is the 95% confidence interval for the mean difference?

Creating a Confidence Interval for the Difference of Two Means with Known Standard Deviations

z*–values for Various Confidence Levels | |

Confidence Level | z*-value |
---|---|

80% | 1.28 |

90% | 1.645 (by convention) |

95% | 1.96 |

#### How do you interpret a 95% confidence interval?

The correct interpretation of a 95% confidence interval is that "we are 95% confident that the population parameter is between X and X."

#### Why is it important to have a normal distribution?

The normal distribution is the most important probability distribution in statistics because many continuous data in nature and psychology displays this bell-shaped curve when compiled and graphed.

#### How do you explain normal distribution?

A normal distribution is the proper term for a probability bell curve. In a normal distribution the mean is zero and the standard deviation is 1. It has zero skew and a kurtosis of 3. Normal distributions are symmetrical, but not all symmetrical distributions are normal.