Analyzing categorical data #2 - Questions and Answers

Question 1 Identify the type of data that would be used to describe a response. Most Watched Television Show Quantitative - Continuous Qualitative (Categorical) Quantitative - Discrete Answer Step 1 Data is of two types. Qualitative Data and Quantitative Data. Qualitative Data - It measures the types of the data. It is about categorical variable, i.e it explains the category of the data. Quantitative Data - It is the numeric data. It represents the numbers. Step 2 Continuous Data - It can take any number of values. It can change over time. Categorical Data - A Categorical Data takes only one value. In this case the value is fixed. Discrete Data - Discrete Data takes certain values. It refers to a number only not a range. Step 3 Most watched television show is a qualitative under categorical data, because this is a type and the value is fixed. Question 2 Explain the differences between categorical and qualitative data. Provide examples. Answer Step 1 Categorical or qualitative data are both the same thing. Both are non-numerical data. Either you say categorical data or qualitative data, both are same. A categorical data or qualitative data represents data types that can be split into groups. Step 2 There are two types of categorical data or qualitative data Nominal and Ordinal data In Nominal, there is no particular order in the categories. For example, In case of Gender we assign male and female. Here male and female are categorical or qualitative data Hair colour we assign brown, black, white, etc. Here Brown, black, white are categorical or qualitative data Weather we can assign sunny, cloudy, snowy, etc. Here sunny, cloudy, snowy are categorical or qualitative data In Ordinal, we assign the label and There is a particular order For example Size of a shirt i.e Small, medium, Large. Here we have assigned the label but at the same time it has particular order. In this Small, medium, Large are categorical or qualitative data Economic Status of a person, we can assign Low, Medium and High. It has a particular order. Here Low, Medium and High are categorical or qualitative data Question 3 Qualitative data that cannot be ranked is called categorical, nominal True False Answer Step 1 Nominal and ordinal data are part of the four data measurement scales in research and statistics, with the other two being an interval and ratio data. These four data measurement scales are subcategories of categorical and numerical data. The Nominal and Ordinal data types are classified under categorical, while interval and ratio data are classified under numerical. This classification is based on the quantitativeness of a data sample. Categorical data is a data type that not quantitative i.e. does not have a number. Therefore, both nominal and ordinal data are non-quantitative, which may mean a string of text or date. Step 2 Nominal data is defined as data that is used for naming or labelling variables, without any quantitative value. It is sometimes called "named" data - a meaning coined from the word nominal. There is usually no intrinsic ordering to nominal data. For example, Race is a nominal variable having a number of categories, but there is no specific way to order from highest to lowest and vice versa. Ordinal data is a type of categorical data with an order. The variables in ordinal data are listed in an ordered manner. The ordinal variables are usually numbered, so as to indicate the order of the list. However, the numbers are not mathematically measured or determined but are merely assigned as labels for opinions. Nominal data is a group of non-parametric variables, while Ordinal data is a group of non- parametric ordered variables. Although, they are both non-parametric variables, what differentiates them is the fact that ordinal data is placed into some kind of order by their position. For example, very hot, hot, cold, very cold, warm are all nominal data when considered individually. But when placed on a scale and arranged in a given order (very hot, hot, warm, cold, very cold), they are regarded as ordinal data. The major character difference between ordinal and nominal data is that ordinal data has a set order to it. This set order is the bedrock of all other character differences between these two data types. For instance, both ordinal and nominal data are evaluated using nonparametric statistics due to their categorical nature. Therefore, the mean and standard deviation cannot be evaluated for these data types. However, the use of parametric statistics for ordinal data may be permissible in some cases. This is done with methods that are a close substitute to mean and standard deviation. Qualitative data that cannot be ranked is called categorical, nominal data. Hence, the given statement is TRUE. Question 4 For each of the following variables, indicate whether they are categorical or numerical. Also, write down what type of graph can be drawn for each. a) Position of a university staff members. b) Weight of participants. C Air temperature on the Celsius scale D) The daily number of code lines written by a programmer Answer Step 1 Categorical data - The variables in data contain groups that are called categorical data. The participants can belong to any one of the group. Numerical data- The data contains only numerical values are called numerical data. They can be as continuous or interval data. Step 2 a) Position of university staff members - categorical data, (as the staff members can belong to any of the various positions in the university). Bar charts, Pie charts can be used to display the data. b) Weight of participants. - numerical data, (as the weight of the person is measured in numerical values). Histograms can be used to display the data. c) Air temperature on the Celsius scale - numerical data, (as the temperature is measured in the numerical values in the celsius scale). Histograms, line graphs, weather graph can be used to display the data. d) The daily number of code lines written by a programmer - numerical data (as the number of code is taken as count in numerical). Histograms can be used to display the data.