Question 1

The dependent variable is what is measured in an experiment. It is the variable that responds to the independent variable.

Accepted Answer

The dependent variable is indeed what is measured and responds to the changes in the independent variable in an experiment.

Question 2

A variable is a characteristic with more than one value.

Accepted Answer

This statement is true. A variable can have multiple possible values, and it is often used to represent a particular characteristic or attribute in a research study or experiment.

Question 3

Statistics are used in quantitative data analysis for two purposes, description, using descriptive statistics, and prediction, using inferential statistics.

Accepted Answer

This statement is true. Descriptive statistics are used to summarize and describe the characteristics of a dataset, while inferential statistics are used to make predictions and generalizations about a larger population based on a sample of data.

Question 4

Basic quantitative data analysis can be carried out by simply adding up of summarising the numbers in a data set.

Accepted Answer

Basic quantitative data analysis often involves summarizing numerical data through measures such as mean, median, mode, and range.

Question 5

Large scale quantitative data sets can be analysed using a computer software package such as SPSS.

Accepted Answer

SPSS is a software package designed specifically for statistical analysis of large data sets. It is commonly used in research, social sciences, and business analysis.

Question 6

Descriptive statistics are used to describe the data gathered.

Accepted Answer

Descriptive statistics are used to summarize and describe data, such as measures of central tendency and variability.

Question 7

In quantitative data analysis the unit of measurement is the variable.

Accepted Answer

In quantitative data analysis, the variable is the unit of measurement. This means that each observation or data point is measured based on the variable being studied. The variable can be a numerical value or a categorical label that defines a characteristic of the data.

Question 8

Experimental design is the methodology used when conducting survey research.

Accepted Answer

Experimental design is a methodology used in experiments, while survey research has its own methodology for data collection and analysis.

Question 9

More complex quantitative data analysis can be carried out using a calculator or a spreadsheet, for example an Excel spreadsheet.

Accepted Answer

Excel spreadsheets can perform various complex quantitative data analysis functions such as regression analysis, correlation analysis, and analysis of variance (ANOVA), making it a useful tool for data analysis.

Question 10

CADA, as well as facilitating data analysis, also served as a tool for managing data.

Accepted Answer

CADA not only helps with data analysis but also provides features for data management.

Question 11

There are different level variables, nominal variables, ordinal variables and interval variables.

Accepted Answer

This statement is true as there are indeed different levels of measurement for variables, including nominal, ordinal, and interval.

Question 12

A dichotomous variable is one that has only two values.

Accepted Answer

A dichotomous variable has only two possible values.

Question 13

In true experiments, the independent variable is manipulated to test whether or not it has an effect on the dependent variable.

Accepted Answer

In true experiments, the researcher actively manipulates the independent variable to see how it affects the dependent variable. This is the defining characteristic of a true experiment.

Question 14

A variable is a characteristic with more than one value.

Accepted Answer

This statement is true. A variable can take on multiple values, which is what makes it useful in data analysis and programming.

Question 15

The independent variable is the variable that is introduced or acted upon in some way in the experiment in order to produce some effect on the dependent variable.

Accepted Answer

This is the correct definition of the independent variable. It is the variable that is manipulated or controlled in an experiment to see how it affects the dependent variable.

Question 16

The analytical framework is the third framework in the four frameworks approach to the research project.

Accepted Answer

The analytical framework is not specifically designated as the third in a universally recognized "four frameworks approach" to research projects. Research methodologies and frameworks can vary widely across disciplines and do not follow a strict order or number.

Question 17

The researcher presents a synopsis of their data analysis in the data analysis chapter, the key findings, the key data, and the key interpretation they have made in relation to the data.

Accepted Answer

This is a standard practice in academic research. The data analysis chapter typically includes a summary of the key findings, the most important data used in the study, and the researcher's interpretation of the data in light of the research questions or hypotheses.

Question 18

Quantitative data is numerical data and quantitative data analysis is the analysis of quantitative data using statistical methods.

Accepted Answer

Quantitative data involves numerical values, such as measurements, counts, or percentages, and quantitative data analysis uses statistical methods to analyze that data.

Question 19

The researcher, steeped in the analysis of the data, plans the data analysis chapter/section, and constructs a framework for this chapter or section. This framework is the analytical framework for the research project.

Accepted Answer

This is true. The researcher needs to plan the data analysis chapter/section and construct a framework for it, which becomes the analytical framework for the research project.

Question 20

Loading data for analysis into a software package is simple work but very precise work. It takes time.

Accepted Answer

Loading data for analysis into a software package requires attention to detail and ensuring the data is properly formatted and organized, so it can take time to do it accurately.

Quiz 14: Analysing Quantitative Data

The dependent variable is what is measured in an experiment. It is the variable that responds to the independent variable.

A variable is a characteristic with more than one value.

Statistics are used in quantitative data analysis for two purposes, description, using descriptive statistics, and prediction, using inferential statistics.

Basic quantitative data analysis can be carried out by simply adding up of summarising the numbers in a data set.

Large scale quantitative data sets can be analysed using a computer software package such as SPSS.

Descriptive statistics are used to describe the data gathered.

In quantitative data analysis the unit of measurement is the variable.

Experimental design is the methodology used when conducting survey research.

More complex quantitative data analysis can be carried out using a calculator or a spreadsheet, for example an Excel spreadsheet.

CADA, as well as facilitating data analysis, also served as a tool for managing data.

There are different level variables, nominal variables, ordinal variables and interval variables.

A dichotomous variable is one that has only two values.

In true experiments, the independent variable is manipulated to test whether or not it has an effect on the dependent variable.

A variable is a characteristic with more than one value.

The independent variable is the variable that is introduced or acted upon in some way in the experiment in order to produce some effect on the dependent variable.

The analytical framework is the third framework in the four frameworks approach to the research project.

The researcher presents a synopsis of their data analysis in the data analysis chapter, the key findings, the key data, and the key interpretation they have made in relation to the data.

Quantitative data is numerical data and quantitative data analysis is the analysis of quantitative data using statistical methods.

The researcher, steeped in the analysis of the data, plans the data analysis chapter/section, and constructs a framework for this chapter or section. This framework is the analytical framework for the research project.

Loading data for analysis into a software package is simple work but very precise work. It takes time.