
Mastering Statistical Analysis in R
Quiz
•
Mathematics
•
University
•
Practice Problem
•
Hard
A.Arokia Lancy
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of hypothesis testing in statistics?
The purpose of hypothesis testing is to determine if there is enough evidence in a sample to infer that a certain condition holds for the entire population.
To summarize data without making any inferences.
To prove a hypothesis is true without any evidence.
To collect data without any statistical analysis.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Explain the difference between Type I and Type II errors.
Type I error: false negative; Type II error: false positive.
Type I error: true negative; Type II error: true positive.
Type I error: false positive; Type II error: false negative.
Type I error: missed detection; Type II error: confirmed detection.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a p-value and how is it interpreted?
A p-value is a measure of the probability that an observed result would occur by chance under the null hypothesis.
A p-value measures the effect size of a statistical test.
A p-value is the probability of the null hypothesis being true.
A p-value indicates the strength of the alternative hypothesis.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Describe the Central Limit Theorem and its significance.
The Central Limit Theorem applies only to small sample sizes.
The Central Limit Theorem states that all populations are normally distributed.
The Central Limit Theorem indicates that sample means will always equal the population mean.
The Central Limit Theorem is a fundamental statistical principle that states that the means of sufficiently large samples from a population will be normally distributed, regardless of the population's distribution.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the difference between parametric and non-parametric tests?
Parametric tests can only be used with small sample sizes, while non-parametric tests can be used with large samples.
Non-parametric tests require a specific distribution; parametric tests do not.
Parametric tests assume a specific distribution; non-parametric tests do not.
Parametric tests are always more accurate than non-parametric tests.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How do you interpret a confidence interval?
A confidence interval shows the exact value of the population parameter.
A confidence interval is a measure of the sample size used in the study.
A confidence interval indicates the probability of a sample mean being accurate.
A confidence interval indicates the range of values that likely contains the true population parameter.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is linear regression and when would you use it?
Linear regression is used for predicting outcomes and understanding relationships between variables.
Linear regression is only used for categorical data analysis.
Linear regression is a method for clustering data points.
Linear regression is primarily used for time series forecasting.
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