Confidence Interval for Diet 1 Mean

In summary, the conversation discusses calculating and interpreting a confidence interval for the sample mean of diet one based on data gathered from 10 independent samples. The sample mean is 100 and the standard deviation is 15.1. The critical value is obtained using a t distribution with 9 degrees of freedom, resulting in a confidence interval of 83.70 to 116.30. This allows for 95% confidence that the true mean of the population for this diet falls within this range.
  • #1
Maybe_Memorie
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Homework Statement



There's no need to write out the full question, but basically we have 6 diets, and for each one a list of the levels of protein in 10 independant samples for each. Sample mean and standard deviation given.

Calculate and interpret a confidence interval centered on the sample mean for diet one.

Homework Equations





The Attempt at a Solution



The sample mean for diet 1 is 100, SD is 15.1

When it says a confidence interval centered on this, do i just calculate

100+-t*(15.1)/root(10) where t* is the critical value obtained using a t distribution with n-1 = 9 degrees of freedom?
 
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  • #2
So the CI will be 83.70 to 116.30? This means we can be 95% confident that the true mean of the population for this diet lies between these two numbers.
 

What is ANOVA confidence interval?

ANOVA confidence interval is a statistical technique used to estimate the range of values within which the true mean of a population lies with a certain degree of confidence. It is used to compare the means of three or more groups and determine if they are statistically different from each other.

Why is ANOVA confidence interval important?

ANOVA confidence interval is important because it allows researchers to determine if there are significant differences between multiple groups and identify which groups are significantly different from each other. This information is crucial in making informed decisions and drawing conclusions from experimental data.

How is ANOVA confidence interval calculated?

ANOVA confidence interval is calculated by taking the mean of each group and then calculating the standard deviation and standard error for each group. These values are then used to calculate the confidence interval, which is typically set at 95% confidence level. This means that there is a 95% chance that the true mean of the population lies within the calculated interval.

What are the assumptions of ANOVA confidence interval?

The assumptions of ANOVA confidence interval include: 1) the data is normally distributed within each group, 2) the variances of the groups are equal, 3) the observations are independent, and 4) the groups are randomly selected from the population. Violation of these assumptions can lead to inaccurate results and conclusions.

How can ANOVA confidence interval be interpreted?

ANOVA confidence interval can be interpreted by looking at the calculated interval and determining if it includes the value of zero. If it does, this means that there is no significant difference between the means of the groups. If the interval does not include zero, then there is a significant difference between the means of the groups. Additionally, the wider the interval, the less precise the estimate of the mean.

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