Members of a gym were asked what kind of training they do. Each of them only did one kind of training. The table shows the results:
| Cardio | Weight | |
|---|---|---|
| Male | 15 | 35 |
| Female | 22 | 8 |
Which variable is the explanatory variable?
Create a row percentage frequency table for this data. Round the values to the nearest percentage.
Does there appear to be an association between the type of training and the gender of gym members?
Does a person’s gender cause them to choose a certain type of training?
Glen surveyed all of the students in Year 12 at his school and summarised the results in the following table:
| Play netball | Do not play netball | |
|---|---|---|
| \text{Height} \geq 170 \text{ cm} | 62 | 138 |
| \text{Height} < 170 \text{ cm} | 60 | 140 |
Which variable is the explanatory variable?
Create a row percentage frequency table for this data. Round the values to the nearest percentage.
A survey was conducted about people's favourite movie genre. The results are shown in the table below:
| Comedy | Action | Drama | Horror | Total | |
|---|---|---|---|---|---|
| Women | 30 | 20 | 45 | 5 | 100 |
| Men | 30 | 40 | 10 | 20 | 100 |
| Total | 60 | 60 | 55 | 25 | 200 |
Which variable is the response variable: movie genre or gender?
To determine if there is an association between the variables is it best to use a row or column percentage frequency table?
Create this frequency table.
Does there appear to be an association between gender and favourite movie genre? Explain your answer.
Mr. Tranor asked his class to pick their favourite subject. He displayed the results in a two-way table:
| Maths | Music | Science | English | |
|---|---|---|---|---|
| Boys | 13 | 9 | 11 | 11 |
| Girls | 20 | 12 | 18 | 11 |
How many girls did not pick maths as their favourite subject?
How many students picked music?
Which variable is the explanatory variable, favourite subject or gender?
To determine if there is an association between the variables is it best to use a row or column percentage frequency table?
Create this frequency table. Round your answers to the nearest percentage.
Does there appear to be an association between gender and favourite subject? Explain your answer.
In a study of car accidents, the following data was found on the number of passengers in the car and whether or not the car rolled over:
| \text{No. passengers:} | \lt5 | 5 - 9 | 10-15 | \gt 15 | \text{Total} |
|---|---|---|---|---|---|
| \text{Roll over} | 335 | 18 | 17 | 2 | 372 |
| \text{No roll over} | 1622 | 42 | 42 | 5 | 1711 |
| \text{Total} | 1957 | 60 | 59 | 7 | 2083 |
Which variable is the explanatory variable?
To examine if there is an association between number of passengers and rollover status, should we use a column or row percentage frequency table?
Create this percentage frequency table for the data. Round your answers to one decimal place.
Based on your table, does there appear to be an association between passengers and rolling over? Explain your answer.
At a local university, students were asked what their favourite subject at high school was and what they have decided to major in at university. The results are shown in the following table:
\text{Favourite subject}| Maths | Science | Music | Art | Total | |
|---|---|---|---|---|---|
| Maths major | 66 | 56 | 21 | 42 | 185 |
| Science major | 51 | 40 | 43 | 25 | 159 |
| Music major | 38 | 33 | 68 | 37 | 176 |
| Art major | 12 | 17 | 48 | 76 | 153 |
| Total | 167 | 146 | 180 | 180 | 673 |
Which variable is the explanatory variable?
To examine if there is an association between favourite subject at school and university major, should we use a column or row percentage frequency table?
Create this percentage frequency table for this data. Round your answers to the nearest percentage.
Does there appear to be an association between favourite subject at school and university major? Explain your answer.
A lecturer commented that “having a favourite subject of mathematics at school causes many students to take mathematics at university”. Is he correct? Explain your answer.
Some students were asked if they are left or right handed. The results are provided in the table below:
| Left-handed | Right-handed | Total | |
|---|---|---|---|
| Men | 8 | 47 | 55 |
| Female | 7 | 65 | 72 |
| Total | 15 | 112 | 127 |
Construct a row percentage two-way table. Round your answers to one decimal place.
Construct a column percentage two-way table. Round your answers to one decimal place.
Maria surveyed a group of people about the type of job they had. She recorded the data in the following graph:
Complete the following two-way table displaying the row percentages:
| None | Casual | Part-time | Full-time | Total | |
|---|---|---|---|---|---|
| Men | 17.6\% | 29.4\% | 41.2\% | 100\% | |
| Women | 22.2\% | 27.8\% | 100\% |
Complete the following two-way table displaying the column percentages:
| None | Casual | Part-time | Full-time | |
|---|---|---|---|---|
| Men | 28.6\% | 62.5\% | ||
| Women | 57.1\% | 37.5\% | ||
| Total | 100\% | 100\% | 100\% | 100\% |
In Australia, 130 random people were surveyed, examining their carbon footprint and the city they lived in. The people were then categorised as living in either an urban or regional location, and whether that person caused high carbon emissions or low carbon emissions. The results are displayed in the table below:
| Urban | Regional | Total | |
|---|---|---|---|
| High emissions | 48 | 20 | 68 |
| Low emissions | 30 | 32 | 62 |
| Total | 78 | 52 | 130 |
Which variable is the explanatory variable, location or emission level?
To examine if there is an association between location and emission levels, should we use a column or row percentage table?
Construct this table for the data. Round your answers to the nearest whole number.
Does there appear to be an association between location and emission level? Explain you answer.
The results of a survey of 279 people on their employment status and gender is shown in the row percentage table:
| None | Part-time | Full-time | Total | |
|---|---|---|---|---|
| Men | 8\% | 17\% | 75\% | 100\% |
| Women | 10\% | 47\% | 43\% | 100\% |
Which variable is the explanatory variable, employment status or gender?
Does there appear to be an association between gender and employment status? Explain your answer.
170 people were surveyed about their music preference. The results have been recorded in the table below:
| Music Preference | Male | Female | Total |
|---|---|---|---|
| \text{Rock and Roll} | 24 | 19 | 43 |
| \text{Classical} | 8 | 15 | 23 |
| \text{Pop} | 17 | 17 | 34 |
| \text{Rap} | 6 | 2 | 8 |
| \text{Country and Western} | 17 | 24 | 41 |
| \text{R and B} | 6 | 9 | 15 |
| \text{Punk} | 4 | 2 | 6 |
| \text{Total} | 82 | 88 | 170 |
What is the explanatory variable in this data set?
Which of the following 100\% stacked column charts should be used to look for an association between the variables?
Does this stacked column chart suggest that there is an association between music preference and gender?
A group of year 12 students surveyed their class and recorded the hair colour and eye colour for each student. The results are displayed in the 100\% stacked column chart shown:
What is the explanatory variable for this chart?
Does the chart suggest an association between eye colour and hair colour?
Can we say that having blue eyes causes a high chance of having blonde hair?
The local library constructed divided bar graphs showing the last six months of book loans by category:
Assume that the total number of loans was exactly the same for each month.
In which month did subscribers borrow the most business books?
Which month was the best month for children's books?
Which variable is the response variable?
Does the divided bar graph suggest that there is an association between the variables?
This stacked column chart shows the fitness levels for various categories of smokers:
What is the response variable for this chart?
Does there appear to be an association between fitness level and category of smoker?
Describe this association.
The following table shows the results of a survey on smoking:
| Smokers | Non-smokers | |
|---|---|---|
| Men | 37 | 69 |
| Women | 51 | 123 |
How many of the people surveyed were smokers?
What percentage of women were non-smokers? Round your answer to the nearest percent.
What percentage of non-smokers were women? Round your answer to the nearest percent.
Which variable is the explanatory variable, smoking status or gender?
To determine if there is an association between the variables is it best to use a row or column percentage frequency table?
Create this percentage frequency table. Round your answers to the nearest percentage.
Create a 100\% stacked column graph for this percentage frequency table.
Does the 100\% stacked column graph indicate an association between the variables? Explain your answer.
A group of people were asked if they are employed and if they have a smartphone. The results are shown in the following table:
| Employed | Unemployed | Total | |
|---|---|---|---|
| Owns a smartphone | 34 | 18 | 52 |
| Does not own a smartphone | 71 | 87 | 159 |
| Total | 106 | 105 | 211 |
Which variable is the explanatory variable, employment or smartphone ownership?
To examine if there is an association between employment and smartphone ownership, should we use a column or row percentage frequency table?
Create this percentage frequency. Round your answers to the nearest percentage.
Does there appear to be an association between employment and owning a smartphone? Explain your answer.
Does a person’s employment status cause them to own a smartphone? Explain your answer.
Create a 100\% stacked column graph for your percentage frequency table.
Does the 100\% stacked column graph indicate an association between the variables? Explain your answer.
118 people were surveyed about their age and how many hours they watch television each week. The results are shown in the following table:
| 10\text{ years }\\ \text{and under} | 11\text{ to }20 \text{ years } | 21\text{ to }30 \text{ years } | 31 \text{ years }\\ \text{or older} | \text{Total} | |
|---|---|---|---|---|---|
| \text{Less than }3\text{ hours} | 9 | 8 | 2 | 5 | 24 |
| 4\text{ to }8 \text{ hours} | 2 | 10 | 2 | 9 | 23 |
| 9\text{ to }15 \text{ hours} | 7 | 8 | 8 | 10 | 33 |
| \text{Over }15 \text{ hours} | 10 | 9 | 9 | 10 | 38 |
| \text{Total} | 28 | 35 | 21 | 34 | 118 |
Which variable is the explanatory variable, age or time spent watching TV?
To examine if there is an association between age and time spent watching TV, should we use a column or row percentage frequency table?
Create this percentage frequency table. Round your answers to two decimal places.
Create a 100\% stacked column graph for this percentage frequency table.
Does the 100\% stacked column graph indicate an association between the variables? Explain your answer.