Statistics: t-Tests and Central Limit Theorem
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Statistics: t-Tests and Central Limit Theorem

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Questions and Answers

What is the appropriate condition to use a Welch t-test instead of a pooled t-test?

  • The variances of the two samples are assumed to be equal.
  • The assumption is that one standard deviation is greater than the other. (correct)
  • The ratio of the standard deviations must be less than 2.
  • The sample sizes must be equal.
  • When should log transformation be considered for datasets?

  • When the number of samples is very high.
  • When the standard deviation is uniform across groups.
  • Only in datasets that are perfectly symmetrical.
  • In one-sample tests with positively skewed data. (correct)
  • What does the ideal result of a log transformation include?

  • Data that maintains its original distribution.
  • A significant decrease in all sample sizes.
  • Two symmetric samples with varying centers and similar spreads. (correct)
  • Symmetric samples with different spreads and similar centers.
  • How is the standard error for the samples’ mean difference calculated in a Welch t-test?

    <p>Using variances and the degrees of freedom as min 𝑛1 − 1, 𝑛2 − 1.</p> Signup and view all the answers

    What occurs when the log-transformed data are symmetric?

    <p>The mean and median are equal.</p> Signup and view all the answers

    What is the purpose of using the t-ratio instead of the z-ratio?

    <p>To make inferences when the population standard deviation is unknown</p> Signup and view all the answers

    In the formula for the standard error of the sample mean, $SE(\bar{Y})$, what does 'n' represent?

    <p>The number of observations in the sample</p> Signup and view all the answers

    Under the Central Limit Theorem (CLT), which distribution is the sample mean approximately normally distributed?

    <p>Sampling distribution of the sample mean</p> Signup and view all the answers

    What is the term for the number of independent values used to estimate $SE(\bar{Y})$?

    <p>Degrees of freedom</p> Signup and view all the answers

    When performing a paired t-test, what is typically being compared?

    <p>Two related samples or matched samples</p> Signup and view all the answers

    What adjustment is made to the standard deviation in the t-ratio when it is unknown?

    <p>It is replaced with the sample standard deviation</p> Signup and view all the answers

    Which of the following is NOT a type of t-test mentioned?

    <p>Independent t-test</p> Signup and view all the answers

    What is the purpose of log-transformation in data analysis?

    <p>To stabilize variance and make a distribution more normal</p> Signup and view all the answers

    What is the null hypothesis for a paired t-test in the context provided?

    <p>The mean difference in scores is equal to 0.</p> Signup and view all the answers

    What does a rejection of the null hypothesis imply in this paired t-test?

    <p>The training module, on average, increased the test scores.</p> Signup and view all the answers

    What is the appropriate formula for the t-ratio in a paired t-test?

    <p>$t-ratio = \frac{d̄}{s_{d} / \sqrt{n}}$</p> Signup and view all the answers

    What is the purpose of calculating the p-value in a paired t-test?

    <p>To help decide whether to reject the null hypothesis.</p> Signup and view all the answers

    How do you calculate the degrees of freedom in a paired t-test?

    <p>By subtracting 1 from the number of observations.</p> Signup and view all the answers

    What is indicated by a p-value less than or equal to alpha (α) in a hypothesis test?

    <p>You reject the null hypothesis.</p> Signup and view all the answers

    Which step is NOT involved in conducting a paired t-test?

    <p>Calculate the standard deviation of the dataset.</p> Signup and view all the answers

    What does the symbol $d$ represent in the context of a paired t-test?

    <p>The mean difference between paired observations.</p> Signup and view all the answers

    What condition indicates that the t-ratio is calculated correctly for a one-sample t-test?

    <p>The standard error is computed using $s/n$.</p> Signup and view all the answers

    What must be true for the t distribution to approach the Z distribution?

    <p>The degrees of freedom must increase.</p> Signup and view all the answers

    In a two-tailed hypothesis test, when is the null hypothesis rejected?

    <p>When the p-value is less than or equal to the level of significance.</p> Signup and view all the answers

    What is the formula to calculate the degrees of freedom in a one-sample t-test?

    <p>$n - 1$</p> Signup and view all the answers

    Which of the following is NOT part of the steps to perform a one-sample t-test?

    <p>Calculate the correlation coefficient.</p> Signup and view all the answers

    What does the term 'null hypothesis' represent in hypothesis testing?

    <p>A statement asserting no effect or no difference exists.</p> Signup and view all the answers

    Which test statistic is used for a right-tail one-sample t-test?

    <p>$t-ratio = rac{Ȳ - μ_0}{s_e}$</p> Signup and view all the answers

    What is the effect of increasing the sample size on the standard error?

    <p>The standard error decreases.</p> Signup and view all the answers

    What does the equation $Med\ Y_m = e^{(Z_m - Z_f)}$ indicate?

    <p>The median salary for males is estimated to be 15.83% more than that for females.</p> Signup and view all the answers

    What is the result of taking the antilog of the difference $ln(Y_m) - ln(Y_f)$?

    <p>It estimates the ratio of the median salaries between males and females.</p> Signup and view all the answers

    How is the confidence interval for the median salary ratio derived?

    <p>It is obtained by exponentiating the lower and upper bounds of $Z_m - Z_f$.</p> Signup and view all the answers

    What does the expression $ln(Y)$ signify in this context?

    <p>The natural logarithm of the population average salary.</p> Signup and view all the answers

    Which of the following statements correctly interprets the results from the analysis?

    <p>The confidence interval indicates that males earn, on average, more than females.</p> Signup and view all the answers

    Why is the expression $ln(Y_m) ≠ ln(Y_f)$ significant?

    <p>It suggests that the logarithmic transformation maintains the order of the data.</p> Signup and view all the answers

    What interpretation can be made from the confidence interval $(e^{0.0996}, e^{0.1942})$?

    <p>The median salary for males might be between 1.11 and 1.21 times that of females.</p> Signup and view all the answers

    What does the term $Z_m$ represent in the analysis?

    <p>The logarithmic transformation of the median salary of males.</p> Signup and view all the answers

    Study Notes

    Introduction

    • Under the central limit theorem (CLT), the sample mean is approximately normally distributed.
    • If the standard deviation of the population (σ) is unknown, we can estimate it using the sample standard deviation (s).
    • The number of independent values used to estimate the standard error of the sample mean (SE(Y)) is called the degrees of freedom (ν).

    t-ratio

    • When the population standard deviation (σ) is known, we use the Z-ratio to make inferences about the population mean.
    • If σ is unknown, we use the sample standard deviation (s) instead and call the ratio the t-ratio.
    • The t-ratio follows a t-distribution with ν = n − 1 degrees of freedom.
    • The t-distribution is symmetrical about its mean of zero, resembling a bell-shaped curve.
    • As the degrees of freedom (ν) increase, the t-distribution approaches the Z-distribution.

    One-Sample t-Test

    • Used for hypothesis testing about the population mean (μ) when σ is unknown.
    • Requires identifying the sample size (n), sample mean (Y), sample standard deviation (s), and the level of significance (α).
    • Define null hypothesis (H0) and alternative hypothesis (H1) to determine the type of test (two-tailed, right-tailed, or left-tailed).
    • Calculate the standard error of the sample mean (se) as s / √n.
    • Calculate the test statistic (t-ratio) as (Y - μ0) / se, where μ0 is the hypothesized population mean.
    • Calculate the degrees of freedom as ν = n - 1.
    • Calculate the p-value based on the t-ratio and degrees of freedom, using appropriate formulas for two-tailed, right-tailed, or left-tailed tests.
    • If the p-value is less than or equal to α, reject H0 and conclude that H1 is true. Otherwise, do not reject H0.

    Paired t-Test

    • Used for hypothesis testing about the difference between two related samples (e.g., pre-test and post-test scores).
    • Define the mean difference as μd = μpost - μpre.
    • Calculate the difference (d) for each observation, where d = Ypost - Ypre.
    • Calculate the mean of d (d̄) and the standard deviation of d (sd).
    • Calculate the standard error of the mean difference (se) as sd / √n.
    • Calculate the test statistic (t-ratio) as d̄ / se.
    • Calculate the degrees of freedom as ν = n - 1.
    • Calculate the p-value based on the t-ratio and degrees of freedom.
    • Reject H0 if the p-value is less than or equal to α.

    Two-Sample t-Test

    • Used for hypothesis testing about the difference between two independent samples (e.g., comparing the means of two groups).
    • Two types: Pooled t-test and Welch t-test.
    • Pooled t-Test: assumes equal variances in both groups.
    • Welch t-Test: does not assume equal variances in both groups.
    • Use the Welch t-test if the ratio of sample standard deviations (s1 / s2) is greater than or equal to 2.

    Log Transformation

    • Used to transform skewed datasets into symmetric ones.
    • Most common choice is the natural logarithm (ln) transformation.
    • Apply log transformation when data is skewed to the right (positively skewed) or when the spread is higher in the group with a larger center (median).
    • Log-transformation aims to create two symmetric samples with similar spreads but potentially different centers.

    Logged Data: Observational Studies

    • After log transformation, if the data is symmetric, then the mean and median of the log-transformed data are equal: Mean[ln(Y)] = Median[ln(Y)].
    • The log transformation preserves order: Median[ln(Y)] = ln[Median Y].
    • By combining these equations, we can estimate the ratio of medians: exp(Z̄m - Z̄f) ≈ (Med Ym) / (Med Yf).
    • The antilog of the difference in means (Z̄m - Z̄f) estimates the ratio of medians in the original data.

    Example – Salary Discrimination

    • Log transformation was applied to salary data to address skewness and facilitate analysis.
    • The difference in log-transformed salaries for males (Zm) and females (Zf) provided an estimate of the ratio of median salaries: exp(Zm̄ - Zf̄) ≈ (Med Ym) / (Med Yf).
    • In the example, the median salary for males was estimated to be 15.83% more than the median salary for females.
    • The 95% confidence interval (CI) for the ratio of medians was also calculated, providing a range of plausible values for the difference in median salaries.

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    Description

    This quiz covers key concepts related to the central limit theorem, t-ratios, and one-sample t-tests. It is essential for understanding hypothesis testing when the population standard deviation is unknown. Test your knowledge on these fundamental statistical principles!

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