Normal Distribution and Confidence Intervals Essay

Submitted By mommym

Words: 418

Pages: 2

Open Document

In Chapter 8 of your text, read the interpretation of confidence intervals. Find a journal article from the library that incorporates repeated sampling. This may be stated or implied. Use the explanation in the last paragraph of the section on interpretation of confidence intervals to describe your data.
After reviewing out text multiple times, I was left clueless as to what exactly “confidence intervals” actually consisted of. I did a little research and came across this definition/explanation from the U.S. Census website that help put things into a little more graspable perspective for myself. Accordingly, the confidence interval is a range of numeric values that describes the uncertainly surrounding an estimate, (U.S. Census, 2013). Confidence intervals are indicated by their endpoints, such as 95% or 90% confidence interval for a particular number of individuals in a sample, representing a level of certainty about an estimate. The confidence intervals contains the average of all estimates a percentage, such as 90% of the time, (U.S. Census, 2013). Ideally, the larger the confidence interval for an estimate, the more caution is required when using the estimate; confidence intervals help define the importance of limitations of estimates, (U.S. Census, 2013).
The study I found pertains to functional asymmetries in the lower-limbs (cited below), which have been at the forefront of many investigations concerning various contact, limited-contact and non-contact sports and their effect on young athletes’ risk for injury. Within the study, samples of young tennis players were randomly divided into an experimental group and control group. Specific tests were used to evaluate functional asymmetries between lower-limbs in strength and speed drill performance. For both groups, the test gave values of P>0.05, which confirmed a normal distribution

Summary 7 Essay

Summary 7 To know population mean reflect on the sample mean, we need to know the sample distribution of the sample mean. Sampling distribution：all possible values that can be assumed by that statistic, computed from samples of the same size drawn from the same population In any particular sample the sample mean (or sample variance) will (almost certainly) not equal to population meanμ (or variance 2) Sampling error: The difference between a sample statistic & the population parameter This error…

Words 413 - Pages 2

Glossary For Exam 2

equal to.” ANOVA (Analysis of Variance): a statistical procedure for testing the equality of multiple means using variances. Central Limit Theorem: The name of the statement telling us that when sampling from a non-Normal population, the sampling distribution of ¯ is approximately Normal whenever the sample is large and x random. Claimed parameter value: The value of the parameter given in the null hypothesis. E.g., μ0 is a claimed parameter value. Conditions: The basic premises for inferential…

Words 843 - Pages 4

Essay on Final Project Statistical Inference

General information about the company 4 Justification of the problem 5 Parameters 6 Models Used 8 Implementing the models 8 Procedure of the Test Process 8 Registered data 10 Capability Histogram 11 Normal Probability Plot 12 Solutions 13 SPC 13 Justification of Model Used 13 Calculations 13 t Distribution 14 Justification of Model Used 15 Calculations 16 Minitab Data 18 Conclusion 20 References 21 Objective The objective of this project is to analyze the data from the testing of the sealability from…

Words 1594 - Pages 7

Essay about TestbankBUAD2060Fall2014 4 PRACTICE

scale of measurement c. ratio scale of measurement d. interval scale of measurement 2.Some hotels ask their guests to rate the hotel's services as excellent, very good, good, and poor. This is an example of the a. ordinal scale of measurement b. ratio scale of measurement c. nominal scale of measurement d. interval scale of measurement 3.Income is an example of a variable that uses the a. ratio scale of measurement b. interval scale of measurement c. nominal scale of measurement d…

Words 9866 - Pages 40

Essay on MATH 159

(n) Binomial Distribution二项分布（5） A specific type of discrete probability distribution that meets these 4 requirements: 1. the process has a fixed # of trials/events 2. The trials/events must be independent of each other 3. Each outcome must have two and only two possible outcomes Commonly labelled “success” and “failure” 4.The probability of a “ success” remains the same across all process trials/events的可能性是相同的“成功”在所有流程试验/事件 Central Limit Theorem（6） The distribution of sample means样本的分布方式…

Words 1611 - Pages 7

business stats Essay

in a company has a normal distribution, with a mean of 35 minutes and a standard deviation of 2 minutes. On 95% of occasions the mailing preparation takes less than how many minutes? invN(.95,35,2) -Lower fence of box-plot= Q1-1.5IQR a population has a normal distribution with a mean of 80 and a standard deviation of 3. Q1=invN(.25,80,3) When drawing a histogram, it is important to label the vertical axis so the reader can determine the counts or percent in each class interval. A set of data has…

Words 1436 - Pages 6

Population Statistics: The Variability Of Sample Populations

sample size ((n). The variability of sample average is decreasing with larger sample size (larger value of n). As gets smaller the sample size (n) gets larger All else being equal, the larger the sample size (n), the steeper/taller/narrower the normal curve (tells us how close we are to the true value). Variability of sample average is larger when the population variance is larger. Larger population variance means our individual draws of the X’s are more spread out. Unbiased – since the expected…

Words 335 - Pages 2

The Study Of Efficiency And Management In A Manufacturing Company

this means that the intervals have an approximately equal width between the minimum (10.030) and maximum (21.980) possible value. This shows us that each of these values is equally likely in the first stage, Time A. The histogram labeled “Histogram of Times A/Times A” in Appendix A shows a pretty symmetric shape of the data. There is no real skewness as our one-variable summary for Times A shows very slight skewness to left of -0.0962, which is very small. The “Q-Q Normal Plot of Times A/Times…

Words 1098 - Pages 5

Essay about Data: Statistics

hypothesis test, regression analysis and others. The descriptive analysis mainly refers to calculate the mean, median, standard deviation, skew and other indicators. T or Z hypothesis test of means or proportions can be used for examining whether the distribution can be explained by the value. The regression analysis mainly aims to research the correlations of the variables, so to find calculate the coefficients of the variables and obtain the final equation (Gorlden, 1936). Therefore, the report mainly…

Words 2256 - Pages 10

Statistics 203A Midterm Exam Question Paper

to construct a 99% confidence interval for the mean m of a normal population with (known) standard deviation s. By using a sample size of 400 rather than 100, you can reduce the margin of error by a factor of 4. (4!2) T F (1 mark) SD is larger than IQR in the standard normal distribution. (SD =1 and IQR =1.35) T F (1 mark) The 10th percentile is for the standard normal distribution approximately 1.28. (1.28!-1.28) T F (1 mark) The standard deviation of a sampling distribution of means is larger than…

Words 412 - Pages 2