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Statistika Quiz

Authored by Aisyah Aisyah

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11th Grade

Statistika Quiz
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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of probability distributions in statistics?

The purpose of probability distributions in statistics is to describe the likelihood of different outcomes in a random experiment or process.

Probability distributions in statistics are used to calculate the mode and median of a dataset.

Probability distributions in statistics are used to determine the mean and standard deviation of a dataset.

Probability distributions in statistics are used to analyze the correlation between variables in a dataset.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the difference between discrete and continuous probability distributions?

Discrete probability distributions and continuous probability distributions are the same thing.

Discrete probability distributions are used for variables that can take on any value within a certain range, while continuous probability distributions are used for variables that can only take on specific values.

Discrete probability distributions are used for variables that can only take on specific values, while continuous probability distributions are used for variables that can take on any value within a certain range.

Discrete probability distributions are used for variables that can take on any value, while continuous probability distributions are used for variables that can only take on specific values.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is hypothesis testing and why is it important in statistics?

Hypothesis testing is a statistical method used to make inferences or draw conclusions about a population based on sample data.

Hypothesis testing is a process of collecting and analyzing data to support a predetermined conclusion.

Hypothesis testing is a technique used to estimate population parameters.

Hypothesis testing is a method used to prove a hypothesis true or false.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Explain the steps involved in hypothesis testing.

Hypothesis testing is a process used to prove a hypothesis is true beyond a reasonable doubt.

Hypothesis testing involves randomly selecting a sample and making conclusions based on that sample alone.

The steps involved in hypothesis testing are: 1. State the null and alternative hypotheses. 2. Set the significance level. 3. Collect and analyze the data. 4. Calculate the test statistic. 5. Determine the critical value or p-value. 6. Make a decision. 7. Draw conclusions.

The steps involved in hypothesis testing are: 1. State the null and alternative hypotheses. 2. Set the significance level. 3. Collect and analyze the data. 4. Calculate the test statistic. 5. Determine the critical value or p-value. 6. Make a decision. 7. Draw conclusions.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is regression analysis and how is it used in statistics?

Regression analysis is used to analyze categorical data in statistics.

Regression analysis is used to model the relationship between variables in statistics.

Regression analysis is used to determine causation between variables in statistics.

Regression analysis is used to predict future outcomes based on historical data in statistics.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the assumptions of linear regression analysis?

Linearity, Independence, Heteroscedasticity, Normality, No multicollinearity

Non-linearity, Dependence, Homoscedasticity, Normality, Multicollinearity

Linearity, Dependence, Homoscedasticity, Normality, No multicollinearity

Linearity, Independence, Homoscedasticity, Normality, No multicollinearity

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the different sampling techniques used in statistics?

random sampling, stratified sampling, cluster sampling, systematic sampling, and convenience sampling

simple random sampling, stratified sampling, cluster sampling, systematic sampling, and convenience sampling

simple random sampling, stratified sampling, cluster sampling, systematic sampling, and convenience sampling

simple random sampling, stratified sampling, cluster sampling, systematic sampling, and convenience sampling

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