How does analyzing data on the real-world problems in the question above aid in problem-solving and drawing conclusions?

QUESTION 1

What is the first step to conducting a statistical study?

Formulate the purpose of the study.

Define the population

Define variables

Analyze results

5 points

QUESTION 2

What is the last step of solving a statistical study?

Collect the data

Interpret the results

Decide what sampling method you will use to collect data

Define variables

5 points

QUESTION 3

From a recent study, it was found that 10% of students travel outside of the country during spring break. Is this an example of descriptive statistics or inferential statistics?

descriptive statistics

Inferential statistics

5 points

QUESTION 4

Which of the following is discrete data?

The number of students attending class on a given day.

Height of a fifth-grade student.

The interest rate charged by a local bank.

The amount of time it takes to travel to work.

5 points

QUESTION 5

Which of the following is continuous data?

The number of marbles in a jar.

The number of computers per household.

Total amount of time it takes to travel to work.

The number of participants in a study.

5 points

QUESTION 6

Which of the following is a categorical (qualitative) variable?

Temperature (in degrees Fahrenheit).

Voting status (registered/non registered).

Distance in miles.

Price of a stock.

5 points

QUESTION 7

Which of the following is a quantitative variable?

Amount in fluid ounce of coffee.

Name of a cell phone carrier.

Occupation.

Anxiety rating (highly anxious, moderately anxious, or relaxed).

5 points

QUESTION 8

A scientist is studying the properties of certain common household materials and how they change with extreme temperatures. She will be collecting data on temperature (in degrees Fahrenheit). What level of measurement is she looking at?

Nominal.

Ordinal.

Ratio.

Interval.

5 points

QUESTION 9

A financial advisor is putting together a report on different Exchanges on which stock is traded (NYSE, AMEX, or other). What type of variable and level of measurement is the advisor using in his report?

Quantitative variable, ordinal variable.

Quantitative variable, nominal variable.

Categorical variable (qualitative), ordinal level of measurement.

Categorical variable (qualitative), nominal level of measurement.

5 points

QUESTION 10

A clothing store is analyzing merchandise prices to help make decisions on what to charge for clothing on clearance. The store owner collects data on the price value (in dollars) of articles of clothing that are on sale/clearance throughout the seasons. What type of variable and level of measurement the owner is looking at?

Quantitative variable, ordinal variable.

Quantitative variable, ratio variable.

Quantitative variable, interval level of measurement.

Categorical variable (qualitative), nominal level of measurement.

5 points

QUESTION 11

Explain the difference between descriptive and inferential statistics and give an example of how each could help you draw a conclusion in the real world.

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10 points

QUESTION 12

You would like to determine whether eating before bed influences your sleep patterns. Describe the steps you would take to conduct a statistical study on this topic.

What is your hypothesis on this issue?
What type of data will you be looking for?
What methods would you use to gather information?
How would the results of the data influence decisions you might make about eating and sleeping?

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10 points

QUESTION 13

A company that sells tea and coffee claims that drinking 2 cups of green tea daily has been shown to increase mood and well being. This claim is based on surveys asking customers to rate their mood on a scale of 1–10 after days they drink/do not drink different types of tea. How would we know if this data is valid and reliable? What questions would you ask to find out more about the quality of the data?

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10 points

QUESTION 14

Identify 1–2 examples of real-world problems that you have observed in your personal, academic, or professional life that could benefit from data-driven solutions. Explain how you would use data/statistics and the steps you would take to analyze the problem. You may also choose topics below (or examples from the weekly content) to help support your response.

Productivity at work.
Financial decisions and budgeting.
Health and nutrition.
Political campaigns.
Quality testing in products.
Human resource policies.
Algorithms for programming/coding.
Accounting and financial policies.
Crime reduction and trends.
Environmental protection/emergency preparedness.