What data science is

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Date:

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Quick Questions

Shade in the A or B circle for each question.

1. Which describes data science?

A Making a guess and hoping it turns out to be right

B Using data to answer questions and make decisions by following a purposeful process

2. A coach wants to know if training twice a week improves sprint times. What is the data science approach?

A Record sprint times before and after training and compare them

B Decide it works because it feels like it does

3. Which is a question that data science could help answer?

A Does average daily temperature affect how many people visit the beach?

B Which colour is the best colour in the universe?

4. A school wants to know if students get enough sleep. Which is data science?

A Assuming students sleep 8 hours because that is the recommendation

B Collecting sleep hours from a sample of students and analysing them

5. True or false: Data science is just guessing with a computer.

A False: it follows a purposeful process using data

B True: a computer just makes better guesses

Match the Pairs

Draw a line connecting each item on the left to its match on the right.

Left column		Right column
1data science		A=AVERAGE(B2:B8)>AVERAGE(B9:B15)
2guessing		BUsing data to answer questions and make decisions by following a purposeful process
3A question that data science could answer in sport: which team scores the most goals per game?		CThis is guessing based on opinion. Data science would collect and check the scores before deciding.
4A data science question about the environment: is this week hotter than last week?		DMaking a decision without checking any evidence, which data science tries to replace
5I think our team is the best, so no need to check the scores.		EThe process is back to front. Data science starts with a clear question and then collects data that helps answer it.
6Collect any data at all, then decide what to ask.		FSELECT team, AVG(goals) FROM games GROUP BY team;

Definitions

data science

Fill in the Blanks

Complete each line of code by filling in the missing parts.

steps ← [8200, 11500, 9800, 12400] avgSteps ← _______(steps)

__ avgSteps >= 10000 THEN OUTPUT "Goal met" ENDIF

question ← "How often does our team win?" percent ← wins / games _ 100

rain ← AVERAGE(readings) ______ "Mean rainfall: " + rain

total ← 0 FOR EACH temp __ temps total ← total + temp

Spot the Error

Shade in the letter of the line that contains an error.

Question 1

A hours = [8, 7, 9, 6]

B total = sum(hours)

C average = total * len(hours)

D print(average)

Question 2

A goals = [2, 0, 3, 1]

B games = len(goals)

C mean = sum(goals) * games

D print(mean)

Question 3

A temps = [31, 35, 29, 38]

B hottest = min(temps)

C print('Hottest:', hottest)

Question 4

A steps = [4000, 8000, 10000

B avg = sum(steps) / len(steps)

C print(avg)

Question 5

A avg_sleep = 6

B if avg_sleep < 8

C print('Sleep more')

Answer Key

What data science is

Section A: Quick Questions

B — Using data to answer questions and make decisions by following a purposeful process

A — Record sprint times before and after training and compare them

A — Does average daily temperature affect how many people visit the beach?

B — Collecting sleep hours from a sample of students and analysing them

A — False: it follows a purposeful process using data

Section B: Match the Pairs

data science → Using data to answer questions and make decisions by following a purposeful process

guessing → Making a decision without checking any evidence, which data science tries to replace

A question that data science could answer in sport: which team scores the most goals per game? → SELECT team, AVG(goals) FROM games GROUP BY team;

A data science question about the environment: is this week hotter than last week? → =AVERAGE(B2:B8)>AVERAGE(B9:B15)

I think our team is the best, so no need to check the scores. → This is guessing based on opinion. Data science would collect and check the scores before deciding.

Collect any data at all, then decide what to ask. → The process is back to front. Data science starts with a clear question and then collects data that helps answer it.

Section C: Definitions

data science — Using data to answer questions and make decisions by following a purposeful process, instead of guessing. For example, using sport or health data to find real answers.

Section D: Fill in the Blanks

steps ← [8200, 11500, 9800, 12400]
avgSteps ← AVERAGE(steps)

IF avgSteps >= 10000 THEN
  OUTPUT "Goal met"
ENDIF

question ← "How often does our team win?"
percent ← wins / games * 100

rain ← AVERAGE(readings)
OUTPUT "Mean rainfall: " + rain

total ← 0
FOR EACH temp IN temps
  total ← total + temp

Section E: Spot the Error

C — The average sleep time is the total divided by the number of values, so it should be total / len(hours). Multiplying gives a number that does not answer the question.

C — The mean goals per game is the total goals divided by the number of games. It should be sum(goals) / games, not multiplied.

B — min() finds the coolest temperature. To answer 'what was the hottest day?' the code must use max(temps).

A — The list is missing its closing square bracket. The line should end with ] so the health data is stored properly.

B — An if statement must end with a colon. It should be if avg_sleep < 8: so the data-based decision runs.