2402 Explanatory Or Response Variables Quiz

In a scatter plot, the y-axis represents the response variable. The response variable is the variable that is being measured or observed and is typically the variable that is affected or influenced by the explanatory variable. The explanatory variable, on the other hand, is usually plotted on the x-axis and is the variable that is believed to have an impact on the response variable. Therefore, the correct answer is that the response variable is shown on the y-axis in a scatter plot.

In a scatter plot, the x-axis represents the variable that is being used to explain or predict the values of the other variable, which is represented on the y-axis. Therefore, the variable shown on the x-axis is the explanatory variable.

The correct answer is "Response Variable". In this example, the grade that a student receives is the variable that we are interested in explaining or predicting. It is the outcome or response that we want to understand the relationship with the number of exercises completed.

In this example, gender is considered the explanatory variable because it is the factor that the politician is using to explain or understand the differences in opinions on environmental policy among the electorate. The politician is surveying both men and women to determine if there is a variation in their opinions based on their gender. By categorizing the respondents based on their gender, the politician is trying to determine if gender has an influence on the opinions regarding environmental policy.

In this example, the teacher wants to determine if there is a relationship between the number of exercises completed and the grade that a student receives. The variable being measured or observed is the grade, which is the response variable. The number of exercises completed is being used to explain or predict the grade, making it the explanatory variable.

In this example, the amount of light each plant received is the explanatory variable. The explanatory variable is the variable that is manipulated or controlled in an experiment in order to determine its effect on the response variable. In this case, the amount of light is being manipulated to see if it has any effect on the growth of the seedlings, which is the response variable.

In this example, the age of the tourists is the explanatory variable. The explanatory variable is the variable that is believed to have an effect on the response variable, which in this case is the type of accommodation (camping or hotel). By surveying the tourists and asking for their age and type of accommodation, the owner can analyze the data and determine if there is a relationship between age and the choice of accommodation.

The variable 'heart rate' is the response variable in this study because it is the outcome or result that is being measured and analyzed. The study is trying to determine if there is a relationship between heart rate and the amount of time spent watching television, so the heart rate is the variable that is being observed and studied.

In this example, weight is the response variable because it is the variable that is being measured or observed. The height of the students is the explanatory variable, as it is the variable that is being used to explain or predict the weight of the students.

In this example, age is the explanatory variable because it is the variable that is being used to explain or predict the response variable, which is whether or not people use mobile internet. By dividing the responses into two age groups (30 and under, and over 30), the provider is trying to determine if age has an impact on the usage of mobile internet.

In this example, the height of the students is being measured in order to determine if there is a relationship between height and weight. Therefore, the height is being used as the explanatory variable, as it is the variable that is believed to have an effect on the weight of the students. The response variable, on the other hand, would be the weight of the students, as it is the variable that is being measured and expected to change in response to the height variable.

The variable 'number of bedrooms' is the response variable because it is the variable that is being predicted or explained by the number of children in a family. The number of bedrooms in a house is dependent on the number of children in a family, and therefore it is the response variable in this investigation.

In this example, the response variable is the time over 100 meters. This is because the time taken by the students to run 100 meters is the outcome or response that we are interested in studying or analyzing. We are trying to determine if there is a relationship between the students' weight and how quickly they run, and the time over 100 meters serves as the response or dependent variable in this analysis.

In this example, the response variable is the opinion on the quality of existing facilities. The response variable is the outcome or the variable that we are interested in studying or predicting. In this case, the researcher is interested in determining whether the students believe the facilities are adequate or not. Therefore, the opinion on the quality of existing facilities is the response variable.

In this example, the response variable is the opinion on switching brands. This is because it is the variable that we are trying to measure or understand based on the customers' responses. The explanatory variable, on the other hand, would be the gender of the customers, as we are splitting them into male and female groups to see if there is any difference in their opinions.

The variable 'number of hours watching television' is the explanatory variable in this study because it is the independent variable that is being manipulated or controlled by the researcher to observe its effect on the dependent variable, which is the heart rate. The researcher is trying to determine if there is a relationship between the amount of time spent watching television and the heart rate, therefore the number of hours watching television is the explanatory variable.

The variable 'population of town' is the explanatory variable because it is the independent variable that is believed to have an effect on the number of jobs available in the town. The explanatory variable is the one that is manipulated or controlled in an experiment or study to determine its relationship with the response variable. In this case, the population of the town is being examined to see if it has an impact on job availability.

In this scenario, the mode of transport is most likely to be the explanatory variable. This is because the mode of transport (train, car, bus, truck, motorcycle, bike, walk) is used to explain or predict the time it takes to travel between Ballarat and Melbourne, which is the response variable. The time taken is influenced by the chosen mode of transport.

In questions involving weight and height, height is considered to be the explanatory variable because it is used to predict or explain weight changes, making weight the response variable. This is because height generally influences weight, with taller individuals typically weighing more due to their larger body mass.

In this example, the type of accommodation (camping at the caravan park or staying in hotel type accommodation) is the response variable. The response variable is the variable that is being measured or observed in a study. In this case, the goal is to find the target audience for advertising hotel accommodation on a surf beach, so the type of accommodation chosen by the tourists is the response variable that will help determine the target audience.

In this example, the smoking status of the surveyed individuals is the response variable. The response variable is the outcome or behavior that is being studied or measured in a research or survey. In this case, the advertising agent is interested in determining whether people smoke or not, and this is the variable that they are investigating. The explanatory variable would be the variable that is believed to have an effect on the response variable, but in this scenario, it is not mentioned or specified.

The given scenario describes the role of the rental real estate agent who collects data from clients and plots the value of the house against the rental returns. In this case, the value of the house is being used as the explanatory variable. The agent is analyzing how the rental returns are influenced or explained by the value of the house. Therefore, the correct answer is "Explanatory Variable."

In a parallel box and whisker plot, the box plots display the explanatory variable. The explanatory variable is the independent variable or the variable that is believed to have an effect on the response variable. It is used to explain or predict changes in the response variable. Therefore, the box plots in a parallel box and whisker plot represent the distribution and variability of the explanatory variable.

When there is a categorical and a numerical variable, we look for a response in the numerical value when the categorical value changes. Categorical is the explanatory variable, Numerical is the response

The variable 'population of rural cities' is the response variable in this investigation. This means that it is the variable that is being measured or observed and is expected to be influenced by the time it takes to travel to Sydney. The population of rural cities is the outcome or result that we are interested in understanding and explaining based on the time it takes to travel to Sydney.

In this example, the independent variable is the location of residence. The hotel owner is surveying tourists to determine if they are from a capital city or a rural area. The location of residence is the variable that the hotel owner is manipulating or controlling in order to gather data and target their advertising towards the appropriate audience.