Spearman's Rho Correlation Quiz

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Questions and Answers

What is the purpose of reporting confidence intervals?

To calculate the p-value

To determine the sample size

To show the range within which the true mean is likely to lie (correct)

To identify the standard deviation

How does the precision of results change with an increase in sample size?

The precision decreases

The precision increases (correct)

The precision becomes unpredictable

The precision remains constant

What does it indicate when confidence intervals do not cross 0?

There is no effect

The standard deviation is high

There is a positive or negative effect (correct)

The sample size is too small

What happens when the confidence interval for ratio scores does not cross 1?

There is no effect Signup and view all the answers

How are p-values and confidence intervals related in statistical inference?

They are complementary and should both be reported Signup and view all the answers

What are inferential statistics used for?

To make predictions about a population based on sample data Signup and view all the answers

What is required for a hypothesis to be testable?

It must enable prediction and be measurable Signup and view all the answers

What does significance testing determine?

The certainty of findings being solely due to chance occurrence Signup and view all the answers

In what situations can we use inferential statistics?

When determining the statistical significance of differences in sample means Signup and view all the answers

What is the purpose of hypothesis testing?

To estimate the average expected outcome of an investigation Signup and view all the answers

When testing the difference between two means, which test should be used for unrelated designs?

Independent t test Signup and view all the answers

Which test is appropriate for investigating an association between two continuous variables?

Persons r Signup and view all the answers

What type of data is suitable for testing with the Chi square test?

Nominal variables Signup and view all the answers

When should the Wilcoxon test be used?

For matched pairs Signup and view all the answers

In what situation would you use a dependent t test?

For related designs Signup and view all the answers

What does a p-value of 0.012 indicate when testing the association between age and SPPBA_TOTAL?

The association is statistically significant Signup and view all the answers

When should an inferential statistical test be applied?

After summarizing and exploring the data Signup and view all the answers

What does a Spearman’s Rho Correlation measure?

Association between ordinal or non-normally distributed scale data Signup and view all the answers

What does a small to moderate association coefficient (0.318) indicate?

The association is weak Signup and view all the answers

What does a p-value of <0.05 indicate about the results of a statistical test?

The Null hypothesis must be rejected Signup and view all the answers

What descriptive statistics should be presented if the data is skewed?

Median and Interquartile Range Signup and view all the answers

In which table are the summary statistics like measures of central tendency and variability traditionally reported?

Table 1 Signup and view all the answers

What type of data should be tested for normality using the Shapiro-Wilk test or Kolmogorov-Smirnov test?

Continuous data only Signup and view all the answers

In which section of the report should you indicate that you have tested the data for normality?

Methods Signup and view all the answers

What type of tests are reported in Table 2 of the report?

Inferential statistical tests Signup and view all the answers

What is the purpose of inferential statistics?

To make assumptions about the population based on the sample data Signup and view all the answers

Which phase of data analysis involves making inferences about the population?

Inferential statistics Signup and view all the answers

Why is it important for the sample to be a good representation of the population in inferential statistics?

To make accurate assumptions about the population Signup and view all the answers

What does inferential statistics allow researchers to do?

To make assumptions about the population based on the sample data Signup and view all the answers

Which type of statistical analysis involves tests and techniques to make inferences about the population?

Inferential statistics Signup and view all the answers

What is the significance level commonly used in statistics to determine if results are statistically significant?

p < 0.05 Signup and view all the answers

What type of error occurs when an effect is claimed, but it actually does not exist in the population?

Type 1 error Signup and view all the answers

Which statistician chose the significance level of p < 0.05 as 'convenient' and 2 standard deviations away from the mean?

Ronald Fisher Signup and view all the answers

What is the probability threshold for results to be considered statistically significant?

5% Signup and view all the answers

When a sample produces a result falling in the accept region and fails to find an effect that actually exists in the population, what type of error is it?

Type 2 error Signup and view all the answers

What is the significance level that some papers might use if they do not want to 'miss' any possible links?

p < 0.1 Signup and view all the answers

What is the term used for finding an effect that really does not exist and was found purely by chance?

False positive Signup and view all the answers

In inferential statistics, what should the sample represent?

The population Signup and view all the answers

Study Notes

Purpose of Confidence Intervals

Confidence intervals provide a range of values within which the true population parameter is expected to fall, offering insights into the reliability of the estimate.
A larger sample size decreases the width of the confidence interval, enhancing the precision of the estimates.

Interpretation of Confidence Intervals

If confidence intervals do not cross 0, it suggests a statistically significant effect exists.
Confidence intervals for ratio scores that do not cross 1 imply a significant effect, indicating a meaningful difference between groups.

Relationship Between p-values and Confidence Intervals

p-values indicate the significance level of a test, while confidence intervals provide a range of plausible values for an effect, helping in the interpretation of results.
Both are tools for statistical inference, aiding in determining the presence of relationships and differences.

Use of Inferential Statistics

Inferential statistics allow researchers to make generalizations about a population based on sample data.
Tests like hypothesis testing assess claims about population parameters.

Requirements for Hypothesis Testing

For a hypothesis to be testable, it must be formulated in a way that allows data to be collected and analyzed, yielding a clear true or false outcome.

Statistical Tests and Applications

When comparing two unrelated means, use the independent t-test.
For investigating the association between two continuous variables, employ Pearson's correlation.
The Chi-square test is suitable for categorical data and evaluating relationships between frequencies.
The Wilcoxon test is appropriate for non-parametric data or when the assumption of normality is violated.
A dependent t-test is utilized when comparing means from the same group at different times.

Understanding p-values

A p-value of 0.012 indicates a statistically significant association between age and a dependent variable (e.g., SPPBA_TOTAL).
A p-value < 0.05 suggests that the results are statistically significant, meaning the null hypothesis can be rejected.

Reporting and Analysis

For skewed data, present median and interquartile ranges as descriptive statistics.
Summary statistics like measures of central tendency and variability are typically reported in a Results table.
Normality tests such as the Shapiro-Wilk or Kolmogorov-Smirnov tests are advisable for continuous data.
Indication of normality testing should be included in the methods section of a report.

Statistical Analysis and Inference

Inferential statistics facilitate making conclusions about a population based on sample findings and include techniques that involve hypothesis testing.
Ensuring samples accurately represent the population is crucial for valid inferences.
The significance level, commonly set at p < 0.05, is used to identify statistically significant results.

Types of Errors in Statistical Testing

Type I error occurs when a significant effect is claimed while none exists in the population.
Type II error arises when a valid effect is not detected due to inadequate power or sample size.
A statistician established p < 0.05 as a convenient threshold for significance, which is two standard deviations from the mean.

General Statistical Concepts

The probability threshold for statistical significance is typically set at p < 0.05.
"False positives" refer to findings of an effect that doesn’t actually exist, leading to misleading conclusions.
In inferential statistics, samples should represent the larger population to ensure accurate conclusions can be drawn.

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Description

Test your knowledge of Spearman's Rho Correlation with this quiz, which includes interpreting correlation coefficients, significance levels, and the types of data suitable for Spearman's Rho. Explore your understanding of the association between variables and its statistical significance.