The Central Limit Theorem is a statistical theory which states that the shape of a sampling distribution is approximately normal no matter the shape of the population when graphed. This theory works as long as the sample size is larger than 30.
To go more into depth to explain this theorem, we could take Grey’s Anatomy fans across the United States track their episode watching habits. They could write down how many episodes they watched a week from the beginning of January to the end June. Below is a graph(taken from the internet, not real data) showing the weeks from January to June as the x axis and showing the number of episodes on the y axis of the data provided by these Grey’s Anatomy fans.
The graph is clearly not normal, yet it
*…show more content…*

Let’s say if I were to keep track of how long I walk my dog if I always take a longer path when I walk the dog during the morning compared to the late afternoon. Putting this data on a graph, it would look binomial like the graph I provided below. Yet just like the Grey’s Anatomy example, if we take the means of multiple random samples from the data and plot it on a graph, it would become normal. Another example where the Central Limit Theorem takes place is if I were to record the pitches that my two dogs bark at. My first dog, Oreo, has a deep, hearty bark where as my second dog, Mya, has a high pitched bark. Considering this, if we graphed their barks, there would be a dip in between which would look similar to the graph right above this paragraph. Yet just like the others, if I was to take multiple random samples from the data and figured out the means of each, it would look much more normal and the dip would be gone. Whether it be using Grey’s Anatomy watching habits, dog walking habits, or the pitch of a dog bark, the Central Limit Theorem can turn a binomial graph into a normal graph. This can be easily done by taking a random sample of over 30 from the data given, taking the means from each sample, and then plotting them on a graph will give us an approximately normal

Related

- Satisfactory Essays
· How were measures of central tendency used in the study? Did the study use the most appropriate measure of central tendency for the given data? Why or why not?

- 761 Words
- 4 Pages

Satisfactory Essays - Satisfactory Essays
## Nt1310 Unit 5 Lab Report Sample

- 106 Words
- 1 Pages

If the population was distributed normally the sample size to be taken will decrease. As the population normally distributes the variance and standard deviation population means will decrease so less number of sample would be appropriate to give good estimates of disease severity to determine the disease epidemics.

- 106 Words
- 1 Pages

Satisfactory Essays - Better Essays
## PSY315 Week Two Practice Problems

- 1080 Words
- 5 Pages

18. Suppose that the scores of architects on a particular creativity test are normally distributed. Using a normal curve table, what percentage of architects have Z scores:

- 1080 Words
- 5 Pages

Better Essays - Decent Essays
## Gke1 Task 2

- 1566 Words
- 7 Pages

It is one of the most popular and well known measures of central tendency. It can be used with both discrete and continuous data, although its use is most often with continuous data

- 1566 Words
- 7 Pages

Decent Essays - Satisfactory Essays
## Qnt 275 Week 1 Statistics In Business Research

- 787 Words
- 4 Pages

• Provide at least two examples or problem situations in which statistics was used or could be used.

- 787 Words
- 4 Pages

Satisfactory Essays - Better Essays
## Is Walmart Safe?

- 1996 Words
- 8 Pages

Iterations of analysis eliminated data points that were listed as “unusual observations,” or any data point with a large standardized residual. After 5 iterations, the analysis showed improved residual plots. Randomness in the versus fits and versus order plots means that the linear regression model is appropriate for the data; a straight line in the normal probability plot illustrates the linearity of the data, and a bell shaped curve in the histogram illustrates the normality of the data.

- 1996 Words
- 8 Pages

Better Essays - Satisfactory Essays
He author also uses statistics to inform the readers with facts. For example he says, “If you’re like the typical owner, you’ll be pulling your phone out 80 times a day.” He uses statistics to inform and persuade the the

- 220 Words
- 1 Pages

Satisfactory Essays - Decent Essays
## Ap Statistics Outline

- 5655 Words
- 23 Pages

standard deviation standardized value rescaling z-score normal model parameter statistic standard Normal model 68-95-99.7 Rule normal probability plot

- 5655 Words
- 23 Pages

Decent Essays - Better Essays
## Normal Distribution and Standard Deviation

- 1399 Words
- 6 Pages

Explain. I don’t think that mine has normal distribution. Mine has a wide range of numbers, but I don’t think that it is distributed like a normal graph should be distributed

- 1399 Words
- 6 Pages

Better Essays - Decent Essays
## The Lady Tasting Te Summary

- 1124 Words
- 5 Pages

The story began in a sunny afternoon in Cambridge in the 1920s. A group of scientists was having a tea party when a lady claimed that there was a difference in taste between the cups where tea was poured into milk and the cups where milk was poured into tea. Sir Ronald Fisher who became a famous statistician suggested an experiment to test the lady’s hypothesis. The story then goes to the 1890s when the statistical revolution started. Karl Pearson was considered by many as the founder of mathematical statistics. Pearson discovered the skew distributions stating that they would cover any type of data scatter and he described these distributions by four numbers; mean, standard deviation, kurtosis and symmetry. Later a Polish mathematician, Jerzy Neyman showed that Pearson’s skew distributions can not be used to explain all possible distributions. Sir Francis Galton who discovered fingerprints was also interested in statistics and he founded a biometrical laboratory to measure height and weights in families to find a mathematical formula that predict the height of children from the heights of their parents. He described regression to the mean where heights of the children moved away from

- 1124 Words
- 5 Pages

Decent Essays - Decent Essays
## Cj / 511 Assignment 2 Assignment 1

- 978 Words
- 4 Pages

This report implements material covered from Chapters 4 – 6: Measures of Central Tendency; Measures of Dispersion; and Probability Distribution. The format in the report uses a question and answer narrative to clarify presentation. The report aims to answer the instructor’s questions for “Assignment 2” and information was extracted from two assigned research studies.

- 978 Words
- 4 Pages

Decent Essays - Decent Essays
## Afl Case Study

- 602 Words
- 3 Pages

Since in a normal distribution, the curve is symmetrical, skewness can affect the accuracy to which normal distribution can be applied to a data set. To determine how close the distribution of the weight of the AFL population is to being normal, the degree of skewness was found as a large degree of skewness would reduce the practicality of applying normal distribution to the data set.

- 602 Words
- 3 Pages

Decent Essays - Satisfactory Essays
## Confidence Intervals Summary

- 203 Words
- 1 Pages

Watching Dr. Pardis Sabeti who is a Computational Geneticist at Harvard University lecture on “Confidence Intervals”. Inference is described as using information from a sample to gather information about a population. Also, she discussed how taking a sample from a population of person with high blood pressure was quite interesting. First you would estimate a population parameter by taking a sample of that person with high blood pressure by taking a blood pressure reading twice and day for one week.

- 203 Words
- 1 Pages

Satisfactory Essays - Decent Essays
## Essay about Statistics in Sports

- 1073 Words
- 5 Pages

Statistical dispersion is measured by a number system. The measure would be zero, if all the data were the same. As the data varies, the measurement number increases. There are two purposes to organizing this data. The first is to show how different units seem similar, by choosing the proper statistic, or measurement. This is called central tendency. The second is to choose another statistic that shows how they differ. This is known as statistical variability. The most commonly used statistics are the mean (average), median (middle or half), and mode (most frequent data). After the data is collected, classified, summarized, and presented, then it is possible to move on to inferential statistics if there is enough data to draw a conclusion.

- 1073 Words
- 5 Pages

Decent Essays - Satisfactory Essays
## Statistics Chapter 7 Homework Essays

- 662 Words
- 3 Pages

Why does the sampling distribution of the mean follow a normal distribution for a large enough sample size, even though the population may not be normally distributed?

- 662 Words
- 3 Pages

Satisfactory Essays