How Scientists Use Data: Data Science at Home Worksheet for Age 16

Free worksheet covering Science, Mathematics, Data Science for age 16 students. Created with Learning Corner's AI-powered tools.

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Instructions

  1. Read each section carefully. Scientists use data to observe patterns, test ideas, and make evidence-based decisions.
  2. Complete the questions using the home-based situations provided.
  3. Show your calculations when asked. A calculator may be used for the final section.
  4. When collecting data at home, protect privacy. Do not record people’s names, passwords, exact locations, or other sensitive information.
  5. For the investigation, collect data for at least 5 days if possible. If not, use the sample data provided.

Learning goals:

  • Distinguish between observations, measurements, and opinions.
  • Identify qualitative and quantitative data.
  • Calculate and interpret mean, median, range, and percentage.
  • Recognize patterns, possible bias, and the difference between correlation and causation.
  • Use data to make a practical recommendation for the home.

1. Scientists and Data

Scientists use a process similar to this:

  1. Ask a focused question.
  2. Decide what data to collect.
  3. Collect data consistently.
  4. Organize and analyze the data.
  5. Look for patterns and unusual results.
  6. Make a conclusion based on evidence.
  7. Communicate the results and identify limitations.

A. Multiple choice

Circle the best answer.

  1. Which question is most suitable for a data investigation?

    a. Is my bedroom nice?

    b. How many minutes does it take for my bedroom to become comfortable after the fan is turned on?

    c. Is blue the best color?

    d. Do people like music?

  2. Which is an example of quantitative data?

    a. The room feels stuffy.

    b. The water looks cloudy.

    c. The washing machine used 42 liters of water.

    d. The meal tasted salty.

  3. Which action improves the reliability of a home investigation?

    a. Measuring only once

    b. Changing several variables at the same time

    c. Using the same measuring method each day

    d. Recording only results that support your prediction

  4. Which statement is an observation rather than an opinion?

    a. The kitchen is too messy.

    b. The kitchen counter has 12 items on it.

    c. The kitchen looks terrible.

    d. Everyone should clean more often.

2. Sort the Data

B. Classify each example

Write qualitative if the data describe qualities or categories. Write quantitative if the data are numbers that can be counted or measured.

  1. The color of food left in the refrigerator: ____
  2. The number of lights switched on at 8:00 p.m.: ____
  3. The smell of a compost container: ____
  4. The amount of water used during a shower: ____
  5. The type of transport used to get home: ____
  6. The temperature inside the house: ____

C. Observation or interpretation?

Write O for observation or I for interpretation.

  1. The living-room window was open at 6:00 p.m. __
  2. Opening the window made the room healthier. __
  3. Three food scraps were placed in the compost container. __
  4. The family wastes too much food. __
  5. The electricity meter reading increased by 4 units. __

3. A Home Data Investigation

A student wants to investigate this question:

How does the time of day affect the temperature in one room?

The student measures the temperature in the same room at the same three times each day.

Day Morning temperature (°C) Afternoon temperature (°C) Evening temperature (°C) Notes
Example: Monday 19 24 21 Sunny afternoon

D. Plan the investigation

  1. What is the independent variable, or factor being compared?

  2. What is the dependent variable, or result being measured?

  3. Name two variables that should be kept the same.

    a. ____

    b. ____

  4. Write a prediction using this structure: If... then... because...

  5. Why should the student measure at the same times each day?

4. Analyze a Data Set

A household tracked the number of minutes that its main lights were switched on each day for one week.

Data: 150, 120, 90, 180, 120, 60, 140 minutes

E. Calculate

  1. Find the total number of minutes.

    Calculation: __

    Answer: ____ minutes

  2. Find the mean, or average, number of minutes.

    Calculation: __

    Answer: ____ minutes

  3. Put the data in order from least to greatest.

  4. Find the median, or middle value.

    Answer: ____ minutes

  5. Find the range.

    Calculation: __

    Answer: ____ minutes

  6. Which day might be unusual if most days had fewer than 150 minutes? Explain.

Helpful formulas:

  • Mean = total of all values ÷ number of values
  • Range = greatest value − smallest value
  • Median = middle value after the data are placed in order

5. Choose the Best Data Display

Match each situation to the most useful display. Write the letter beside each number.

  • A. Bar chart
  • B. Line graph
  • C. Pie chart
  • D. Scatter plot
  1. Comparing the number of plastic, paper, metal, and glass items recycled: __
  2. Showing how indoor temperature changes throughout a day: __
  3. Showing the percentage of a monthly household budget spent on different categories: __
  4. Investigating whether hours of sleep are related to time spent using a phone: __

F. Design a graph

Use the light-use data from Section 4 to sketch a graph on paper.

  • Choose a suitable graph type.
  • Label both axes, including units.
  • Add a clear title.
  • Plot all seven values.
  • Circle the highest value and explain what it may show.

Graph title: __

What does the highest value show?

6. Data Science in Context

Data science combines asking questions, collecting data, organizing data, finding patterns, and communicating conclusions. It is used in many everyday decisions.

G. Match the data science task to the home example

Write the correct letter beside each number.

  • A. Collecting data
  • B. Cleaning data
  • C. Finding a pattern
  • D. Making a prediction
  • E. Communicating results
  1. Recording the amount of food thrown away each evening: __
  2. Correcting a typing error that says 500 liters instead of 50 liters: __
  3. Noticing that food waste is greatest on evenings when no meal plan was made: __
  4. Estimating next week’s food waste using previous records: __
  5. Creating a chart and short report for the household: __

H. Evaluate the conclusion

A student notices that the household uses more electricity on rainy days. The student concludes:

Rain causes the household to use more electricity.

  1. Is this conclusion fully justified? Explain.

  2. Give one other possible explanation for the pattern.

  3. What additional data would help test the explanation?

7. Home Investigation Challenge

Choose one investigation, or create your own practical question.

  • Does taking shorter showers reduce the household’s water use?
  • Which room loses heat fastest after the heating is turned off?
  • How much food is wasted before and after meal planning?
  • Does placing reusable bags near the door increase their use?
  • How does screen time relate to bedtime on school nights?

Investigation planner

  1. My question:

  2. My prediction:

  3. What data will I collect?

  4. What unit will I use? For example, minutes, liters, grams, degrees Celsius, or number of items.

  5. How often will I collect the data?

  6. What will I keep the same to make the investigation fair?

  7. What safety or privacy issue should I consider?

  8. After collecting the data, I will use this display:

  9. My evidence-based conclusion will be:

  10. One limitation of my investigation is:

8. Reflection

Answer in complete sentences.

  1. How could data help someone save money or resources at home?

  2. Why is it important to record data even when the results do not match your prediction?

  3. What is one data investigation you could repeat every month to help your household make a better decision?

Optional Challenge

A household used 240 liters of water on Monday, 210 liters on Tuesday, 260 liters on Wednesday, 190 liters on Thursday, and 200 liters on Friday.

  1. Calculate the mean daily water use.

  2. The household wants to reduce its mean use by 15%. How many liters would the new target be?

  3. Suggest one change that could reduce water use. Explain how you would collect data to test whether it worked.

Answer Key

1. Scientists and Data

A. Multiple choice

  1. b
  2. c
  3. c
  4. b

2. Sort the Data

B. Classify each example

  1. Qualitative
  2. Quantitative
  3. Qualitative
  4. Quantitative
  5. Qualitative
  6. Quantitative

C. Observation or interpretation?

  1. O
  2. I
  3. O
  4. I
  5. O

3. A Home Data Investigation

D. Plan the investigation

  1. The time of day, such as morning, afternoon, or evening.
  2. The temperature of the room in degrees Celsius.
  3. Acceptable answers include the same room, the same thermometer, the same measurement location, and the same measurement method.
  4. Example: If the time of day changes from morning to afternoon, then the temperature will usually be higher in the afternoon because sunlight and outdoor heating warm the room.
  5. Measuring at the same times makes the comparison fairer and reduces the effect of time differences.

4. Analyze a Data Set

E. Calculate

  1. Total: 150 + 120 + 90 + 180 + 120 + 60 + 140 = 860 minutes
  2. Mean: 860 ÷ 7 = 122.86 minutes, or approximately 123 minutes
  3. Ordered data: 60, 90, 120, 120, 140, 150, 180
  4. Median: 120 minutes
  5. Range: 180 − 60 = 120 minutes
  6. 180 minutes may be unusual because it is the greatest value and is higher than most of the other daily values.

5. Choose the Best Data Display

  1. A. Bar chart
  2. B. Line graph
  3. C. Pie chart
  4. D. Scatter plot

F. Design a graph

Answers will vary in appearance. The graph should have a suitable title, labeled axes with units, all seven data points, and the highest value of 180 minutes clearly identified. The highest value represents the day with the greatest recorded light use; it may indicate a longer period of activity, more people at home, or another factor that should be investigated.

6. Data Science in Context

G. Match the data science task

  1. A
  2. B
  3. C
  4. D
  5. E

H. Evaluate the conclusion

  1. No. The data may show a relationship, but they do not prove that rain caused the increased electricity use.
  2. Possible answers include people staying indoors more, using more lights, using heating or cooling, watching more television, or cooking more often.
  3. Useful additional data could include rainfall amount, time spent at home, heating or cooling use, number of lights used, and electricity use on sunny and rainy days over several weeks.

7. Home Investigation Challenge

Answers will vary. A strong response should include a focused question, a testable prediction, measurable data with units, a consistent method, control of important variables, attention to safety and privacy, a suitable graph or table, an evidence-based conclusion, and at least one limitation.

8. Reflection

Answers will vary. Strong answers should connect data to practical decisions, explain why honest recording supports reliable conclusions, and suggest a repeatable monthly investigation.

Optional Challenge

  1. Total water use: 240 + 210 + 260 + 190 + 200 = 1,100 liters. Mean: 1,100 ÷ 5 = 220 liters per day.
  2. A 15% reduction is 220 × 0.15 = 33 liters. New target: 220 − 33 = 187 liters per day.
  3. Answers will vary. A complete response should suggest a measurable change, such as shorter showers, and compare water-use data before and after the change while keeping the collection method consistent.
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