Basic Statistics

The quiz is about MCQs Data and Variables with Answers. There are 20 multiple-choice questions covering the topics related to variables, data, types of data (such as discrete or continuous, quantitative or qualitative), and level of measurements. Let us start with the MCQs Data and Variables Statistics Quiz.

Online MCQs Data And Variables Quiz with Answers

• The age of the individual was recorded at the time of the survey. What type of variable would age be considered?
• The adult indicator variable is coded as a 1 if the individual is 18 or older and a 0 if not. What type of variable would the adult indicator variable be considered?
• In a survey, employees were asked to report their typical daily commute time, in minutes. What type of variable would their response be considered?
• In a survey, employees were asked to report their typical daily mode of transportation to and from work (i.e. Car, Bike, Bus, etc.). What type of variable would their response be considered?
• In a survey, the company wanted to know how employees perceived the work of upper management. Employees were asked to report the satisfaction of upper management using a 1 to 5 scale (with the following representations:

1. Extremely Unsatisfied,
2. Unsatisfied,
3. Neutral,
4. Satisfied,
5. Extremely Satisfied)

• What type of variable would their response be considered? https://gmstat.com
• In a survey, it was reported that Fridays were generally lighter regarding the number of meetings held. Employees were asked to report the number of scheduled meetings they attended the previous Friday. What type of variable would their response be considered?
• In a survey, management was playing around with the idea of having a food truck visit the office once a week and was trying to gauge how much employees would spend to help entice various food truck owners. Employees were asked to report the amount of money they believed they would spend on lunch (in $XX.XX) if a food truck came to the office once a week. What type of variable would their response be considered?
• Library cardholders were asked whether or not they had checked out a book from the library in the past month (yes or no). What type of variable would their response be considered?
• Library cardholders were asked to report the amount of late fees they have been charged in the past year (input in the form of $XX.XX). What type of variable would their response be considered?
• Library cardholders were asked to reflect on the most recent book they checked out and report the genre that it most closely represented (i.e. Science Fiction, Action, Romance, Mystery, etc.). What type of variable would their response be considered?
• The library recently added a new online checkout/renewal system. Library cardholders were asked how many times they had used the new online system. What type of variable would their response be considered?
• Library card holders were asked to report the satisfaction of their library experience during their last visit using a 1 to 5 scale (with the following representations:

1. Extremely Unsatisfied,
2. Unsatisfied,
3. Neutral,
4. Satisfied,
5. Extremely Satisfied).

• What type of variable would their response be considered?
• Focus groups, individual respondents, and panels of respondents are classified as
• Reports on quality control, production, and financial accounts issued by companies are considered as
• The type of rating scale that allows respondents to choose the most relevant option out of other stated options is classified as
• Data which is generated within the company such as routine business activities is classified as
• The scale which is used to determine ratio equality is considered as
• Measurement scale which allows researchers and statisticians to perform certain operations on data collected from respondents is classified as
• The type of questions included in the questionnaire to record responses in which respondents can answer in any way are classified as
• Measurement scale which allows ranking of numbers rather than arithmetic operations on data is classified as

MCQs General Knowledge

The post is about Classification in Data Mining. It is in the form of questions and answers for easy of understanding and learning the classification techniques and their applications in real-life.

What is Classification in Data Mining? Explain with Examples.

Classification in data mining is a supervised learning technique used to categorize data into predefined classes or labels based on input feature data. The classification technique is widely used in various applications, such as spam detection, image recognition, sentiment analysis, and medical diagnosis.

The following are some of the real life examples that make use of classification algorithms:

• A bank loan officer may need to analyze the data to know which customers are risky or which are safe.
• A marketing manager may need to analyze a customer with a given profile, who will buy a new product item.
• Banks and financial institutions use classification algorithms to identify potentially fraudulent transactions by classifying them as “Fraudulent” or “Legitimate” transactions based on transaction patterns.
• Mobile apps and digital assistants use classification algorithms to convert handwritten text into digital format by identifying and classifying individual characters or words.
• News channels and companies use classification algorithms to categorize their articles into different sections (such as Sports, Politics, Business, Technology, etc.) based on the content of the articles.
• Businesses analyze customer reviews, feedback, and social media posts to classify sentiments as “Positive,” “Negative,” or “Neutral,” helping them gauge public perception about their products or services.

What is the Goal of Classification?

Classification aims to develop a model that can accurately predict the class of unseen instances based on patterns learned from a training dataset.

Write about the Key Components of Classification.

Key components of classification in Data Mining are:

1. Training Data: A dataset where the class labels are known, which will be used to train the classification model.
2. Model: An algorithm (such as decision trees, neural networks, support vector machines, etc.) that learns to distinguish between different classes based on the training data.
3. Features: The input variables or attributes that are used to make predictions about the class labels.
4. Prediction: Once a model is trained, the model can classify new, unseen instances by assigning them to one of the predefined classes.
5. Evaluation: The performance of the classification model can be assessed using metrics like accuracy, precision, F1 score, recall, and confusion matrix.

Why Classification is Needed?

In today’s world of Big Data, a large dataset is becoming a norm. For example, image a dataset/database with many terabytes such as Facebook alone crunches 4 Petabyte of data every single day. On the other hand primary challenge of big data is how to make sense of it. Moreover, the sheer volume is not the only problem. also, big data needs to be diverse, unstructured, and fast changing.

Similalry, consider the audio and video data, social media posts, 3D data or geospatial data. These kind of data are not easy to categorize or organized.

Name Methods of Classification Methods

The following are some population methods of classification methods.

• Statistical procedure based approach
• Machine Learning based approach
• Neural network
• Classification algorithms
• ID3 algorithm
• 4.5 Algorithm
• Nearest neighbour algorithm
• Naive bayes algorithm
• SVM algorithm
• ANN algorithm
• Deision Trees
• Support vector machine
• Sense Clusters (an adaption of the K-means clustering algorithm)

Explain ID3 Algorithm

The ID3 (Iterative Dichotomiser 3) algorithm is a decision tree learning algorithm, primarily used for classification tasks in data mining and machine learning.

What are the Key Features of ID3 Classification?

• Categorical Attributes: ID3 algorithm is designed to work primarily with categorical attributes. It does not handle continuous attributes directly, but they can be converted into categorical ones through binning.
• Information Gain: The algorithm uses information gain as a criterion to select the attribute that best separates the data into different classes. Information gain measures the reduction in entropy (uncertainty) after a dataset is split based on a specific attribute.
• Recursive Tree Building: ID3 classification algorithm builds the decision tree recursively, splitting the data into subsets based on attribute values.

MCQs Data Mining

Data Analysis in R Programming Language

The post is about MCQs introduction to Statistics. There are 20 multiple-choice questions in this quiz related to data, variables, measures of central tendencies, measures of dispersions, level of measurements, and measures of positions. Let us start with the MCQs Introduction to Statistics Quiz.

Please go to MCQs Introduction to Statistics 21 to view the test

Online MCQs Introduction to Statistics

• A researcher wants to measure physical height in as much detail as possible. Which level of measurement does s/he employ?
• Suppose a researcher conducted a study on eye color and 550 people are questioned about it. 110 of them have brown eyes and 44% of them have blue eyes. What percentage of the people you questioned have blue or brown eyes?
• Ten students completed an exam. Their scores were: 5, 7, 2, 1, 3, 4, 8, 8, 6, 6. What is the interquartile range (IQR)?
• A researcher wants to know what people think of football. He asks ten people to rate their attitude towards football on a scale from 0 (do not like football at all) to 10 (like football a lot). The ratings from ten people are as follows: 1, 10, 6, 9, 2, 5, 6, 6, 5, 10. What is the standard deviation?
• Which of the following statements is true? I. The larger the variance, the smaller the standard deviation. II. The stronger the skew, the smaller the difference between the median and the mean.
• The grades for a statistics exam are as follows: 3, 5, 5, 6, 7.5, 6, 5, 1, 10, 4. Which score is an outlier? Use the interquartile range (IQR).
• How many goals have the top strikers in a football competition scored? For the following 10 strikers, the information obtained is: 12, 10, 11, 12, 11, 14, 15, 18, 21, 11. The (1) ———— of the dataset equals 12, the mean equals (2) ———–, and the (3) ————– equals 11. The standard deviation equals (4) ———— Fill in the right words/numbers.
• What is true about a variance of zero?
• What is the difference between variables and constants?
• A population mean is a center of mass of what?
• A sample mean is a center of mass of what?
• A population mean estimates a sample mean.
• A sample mean is unbiased.
• The more data that goes into the sample mean, the more concentrated its density/mass function is around the population mean.
• What type of data refers to information obtained directly from the source?
• Data obtained from an organization’s internal CRM, HR, and workflow applications is classified as:
• When you detect a value in your data set that is vastly different from other observations in the same data set, what would you report that as?
• The height of a student is 60 inches. This is an example of ——————?
• If a Curve has a longer tail to the right, it is called
• The extent to which values are dispersed around central observation is considered as

Computer MCQs Online Test