Demographic data for statistical analysis
Name:
Date:
Class:
A
Quick Questions
Shade in the A or B circle for each question.
1. Which of these is an example of demographic data?
2. Why do analysts collect demographic data?
3. A table shows the number of people in each age group: 0-17, 18-34, 35-64 and 65+. Which sub-theme is this?
4. Which pair of fields would let you compare average income between regional Victoria and Melbourne?
5. True or false: Demographic data can be used to compare the percentage of people with a university degree in two different suburbs.
B
Match the Pairs
Draw a line connecting each item on the left to its match on the right.
| Left column | Right column | |
|---|---|---|
| 1demographic data | AData describing characteristics of a population, such as age, location, income and education, so groups can be compared | |
| 2age_group = "18-24" | BOne person from each group is not a statistical comparison. Groups should be compared using totals, averages or percentages across all members. | |
| 3Comparing average income between two locations uses demographic data on location and income | CA demographic field that places each person in an age band so age groups can be compared | |
| 4Counting how many people fall into one age group is a statistical way to compare groups | DFavourite songs are personal preferences, not demographic characteristics. Demographic data covers age, location, income and education. | |
| 5Demographic data = a list of each person's favourite songs | EAVERAGEIF(B2:B100,"Geelong",C2:C100) | |
| 6Comparing two age groups using one person's income from each | FCOUNTIF(A2:A100,"25-34") |
C
Definitions
demographic data
D
Fill in the Blanks
Complete each line of code by filling in the missing parts.
1.
=_______(B2:B100,"18-24")
2.
=_________(C2:C100,"Geelong",D2:D100)
3.
=COUNTIF(D2:D100,"_50000")
4.
=COUNTIF(B2:B100,"18-24")/______(B2:B100)
5.
=MAX(D2:D100)-___(D2:D100)
E
Spot the Error
Shade in the letter of the line that contains an error.
Question 1
A
ages ← [16, 25, 41, 67]
B
total ← 0
C
FOR EACH ages IN a
D
total ← total + a
E
avg ← total / 4
Question 2
A
young ← 0
B
older ← 0
C
FOR EACH a IN ages
D
IF a < 25: young ← older+1
E
ELSE older ← older + 1
Question 3
A
=COUNTIF(C:C,"Vic")
B
=COUNTIF(C:C,"NSW")
C
=AVERAGEIF(D:D,"Vic",C:C)
Question 4
A
avgVic ← AVERAGE(incomeVic)
B
avgNSW ← AVERAGE(incomeNSW)
C
diff ← avgVic - avgNSW
D
IF diff < 0 THEN
E
DISPLAY "Vic is higher"
Question 5
A
age ← 15
B
IF age > 18 THEN
C
group ← "Youth"
D
ELSE
E
group ← "Adult"
Answer Key
Demographic data for statistical analysis
Section A: Quick Questions
Q1
A — A person's age group, such as 25-34
Q2
B — So different groups can be compared and analysed statistically
Q3
A — Age groups
Q4
B — Location and income
Q5
A — True
Section B: Match the Pairs
Q1
demographic data → Data describing characteristics of a population, such as age, location, income and education, so groups can be compared
Q2
age_group = "18-24" → A demographic field that places each person in an age band so age groups can be compared
Q3
Comparing average income between two locations uses demographic data on location and income → AVERAGEIF(B2:B100,"Geelong",C2:C100)
Q4
Counting how many people fall into one age group is a statistical way to compare groups → COUNTIF(A2:A100,"25-34")
Q5
Demographic data = a list of each person's favourite songs → Favourite songs are personal preferences, not demographic characteristics. Demographic data covers age, location, income and education.
Q6
Comparing two age groups using one person's income from each → One person from each group is not a statistical comparison. Groups should be compared using totals, averages or percentages across all members.
Section C: Definitions
Q1
demographic data — Data describing characteristics of a population, such as age, location, income and education, so that different groups can be compared and analysed statistically.Section D: Fill in the Blanks
Q1
=COUNTIF(B2:B100,"18-24")Q2
=AVERAGEIF(C2:C100,"Geelong",D2:D100)Q3
=COUNTIF(D2:D100,">50000")Q4
=COUNTIF(B2:B100,"18-24")/COUNTA(B2:B100)Q5
=MAX(D2:D100)-MIN(D2:D100)Section E: Spot the Error
Q1
C — The loop variable and the list are swapped. It should be FOR EACH a IN ages so each age in the age data is added to the total.}},
Q2
D — People under 25 belong in the young age group, so the young counter must increase. It should be young ← young+1.
Q3
C — The ranges are swapped. The location column (C) is the criteria range and the income column (D) is the range to average: =AVERAGEIF(C:C,"Vic",D:D).
Q4
D — A positive difference (avgVic - avgNSW) means Victoria's average income is higher. The test should be diff > 0.
Q5
B — The comparison is reversed, so a 15-year-old would be put in the Adult group. It should be IF age < 18 THEN.