STU-SIT Quiz on Statistical Analysis
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Questions and Answers

Which statistical technique should be used to test if there is a statistically significant difference in the mean ratings for AA hotel and BB hotel?

  • T-test (correct)
  • Chi-square test
  • Paired t-test
  • Kruskal-Wallis test

The MPAA rating is considered a nominal scale.

False (B)

What measurement scale is used for the feature 'Total Gross'?

ratio

The variable 'Release Date' is measured on the ___ scale.

<p>interval</p> Signup and view all the answers

Match the following features with their corresponding measurement scales:

<p>Genre = Nominal Release Date = Interval Total Gross = Ratio MPAA Rating = Ordinal</p> Signup and view all the answers

In a regression analysis, which variable is likely to be insignificant at a 95% significance level?

<p>Independent variable with p-value greater than 0.05 (D)</p> Signup and view all the answers

The Kruskal-Wallis test is suitable for comparing more than two independent groups.

<p>True (A)</p> Signup and view all the answers

Which of the following techniques is NOT suitable for tumor cell detection in x-ray images?

<p>Linear Regression (B)</p> Signup and view all the answers

What is the primary purpose of a Chi-square test?

<p>To test the independence of categorical variables</p> Signup and view all the answers

All forms of data can be classified as either structured, semi-structured, or unstructured.

<p>True (A)</p> Signup and view all the answers

Name one advantage of using Neural Networks for detecting tumor cells.

<p>Neural Networks can learn complex patterns in data.</p> Signup and view all the answers

PDF file format is developed by Adobe to present documents independent of __________.

<p>application software, hardware and operating systems</p> Signup and view all the answers

Which of the following best describes a structured data type?

<p>Data organized into a predefined model (D)</p> Signup and view all the answers

A decision tree is a type of regression model.

<p>False (B)</p> Signup and view all the answers

How does the repetition of processes affect data classification?

<p>Data may be classified as repetitive or non-repetitive.</p> Signup and view all the answers

Match the following data types with their characteristics:

<p>Structured = Organized with a predefined schema Semi-structured = Contains both fixed and variable fields Unstructured = Not organized in a pre-defined format Repetitive = Generated from recurrent processes</p> Signup and view all the answers

Which statement is true regarding the population trends in Singapore from 1990 to 2015?

<p>There is a spike in the Total Fertility rate for the year 2000. (D)</p> Signup and view all the answers

The Total Fertility rate in Singapore has shown a consistent increase from 1990 to 2015.

<p>False (B)</p> Signup and view all the answers

What percentage of the age column is missing in the employee data?

<p>90%</p> Signup and view all the answers

It is suggested to __________ the missing age value using k-NN.

<p>impute</p> Signup and view all the answers

What is an appropriate data manipulation step for handling a column with 90% missing values?

<p>Impute the missing age value using k-NN. (A), Impute the missing age value using the mean age. (C)</p> Signup and view all the answers

Replacing missing values with a new category 'missing' is a valid data manipulation technique.

<p>True (A)</p> Signup and view all the answers

Match the methods of data preparation with their descriptions:

<p>Imputation using k-NN = Statistical method that predicts missing values based on similar records Mean imputation = Replacing missing values with the average of available data Eliminating records = Removing rows with missing values from the dataset Categorical replacement = Creating a new category for missing data</p> Signup and view all the answers

What statistical analysis method would you use to determine the significance of the difference in meal costs?

<p>t-test or ANOVA</p> Signup and view all the answers

What does the Certificate of Entitlement (COE) in Singapore allow an individual to do?

<p>Own and operate a vehicle (B)</p> Signup and view all the answers

The number of available COEs in each category is fixed and does not change.

<p>False (B)</p> Signup and view all the answers

What method is used to visualize the number of monthly confirmed cases?

<p>Data visualization</p> Signup and view all the answers

The outcome variable in the predictive model is the __________ Indicator.

<p>Response</p> Signup and view all the answers

Match the following data visualization components with their purposes:

<p>Heat map = Mode of shipping Line chart = Trend over time Bar chart = Comparison between categories Pie chart = Proportion of parts to a whole</p> Signup and view all the answers

Which of the following is a potential issue with the input selection for the predictive model?

<p>Inputs lack diversity (A), Response variable is irrelevant (B), Inputs are not correlated with outcome (D)</p> Signup and view all the answers

Visualizations should always be complicated to ensure thorough data representation.

<p>False (B)</p> Signup and view all the answers

Suggest a way to improve a heat map visualization.

<p>By adding labels or scaling colors for better interpretation.</p> Signup and view all the answers

What is the primary purpose of creating visualizations for the Superstore dataset?

<p>To determine marketing strategy variations (A)</p> Signup and view all the answers

The visualizations should include a comparison of sales by product category and customer loyalty.

<p>False (B)</p> Signup and view all the answers

What factor is multiplied to determine sales in the Superstore dataset?

<p>Selling price and quantity</p> Signup and view all the answers

The visualizations for investigating the proportion of product category bought should focus on _____ sold.

<p>quantity</p> Signup and view all the answers

Match the following visualization purposes with their descriptions:

<p>Comparison of sales = To determine effective marketing strategies Proportion of product category = To understand purchasing behavior by region Investigate selling price = To analyze price differences across segments and regions</p> Signup and view all the answers

What is the main purpose of analyzing the relationship between advertisements and website traffic?

<p>To assess marketing effectiveness (A)</p> Signup and view all the answers

The exhibits provide adequate information to determine if increased advertisements cause increased website traffic.

<p>False (B)</p> Signup and view all the answers

What type of chart would best illustrate the relationship between the number of advertisements and website traffic?

<p>Scatter plot</p> Signup and view all the answers

The y-axis of the suggested chart should represent _____ and the x-axis should represent _____ in analyzing the advertisements and website traffic.

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What information is crucial for determining whether increased advertisements affect website traffic?

<p>The monthly trends of website visitors and advertisements (C)</p> Signup and view all the answers

The exhibits provide all necessary information to conclude that increased advertisements lead to increased website traffic.

<p>False (B)</p> Signup and view all the answers

What type of chart would be most effective in illustrating the relationship between the number of advertisements and website traffic?

<p>Scatter plot</p> Signup and view all the answers

Match the following types of data with their corresponding characteristics:

<p>Structured Data = Organized in a predefined format with identifiable patterns Unstructured Data = Information that does not have a predefined data model Semi-structured Data = Contains elements of both structured and unstructured data Qualitative Data = Descriptive information that cannot be measured numerically</p> Signup and view all the answers

Which of the following is a valid method for checking data quality in the Sales dataset?

<p>Identifying duplicates in customer entries (B)</p> Signup and view all the answers

Replacing missing values with their mean is always the most accurate method of data cleaning.

<p>False (B)</p> Signup and view all the answers

What should be done to replace missing values for the monthly_premium column?

<p>Replace with the mean value of the column</p> Signup and view all the answers

Flashcards

Logistic Regression

A statistical method used to predict the probability of a binary outcome (e.g., yes/no, positive/negative).

Decision Tree

A supervised machine learning algorithm that uses a tree-like structure to classify data based on a series of rules.

Neural Network

A machine learning model inspired by the human brain, capable of learning complex patterns in data.

Linear Regression

A statistical technique that models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

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Support Vector Machine

A supervised machine learning model used for classification and regression tasks. It aims to find the best hyperplane to separate data points of different classes.

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Structured data

Data organized in a predefined format, often in tables or databases.

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Unstructured data

Data that does not have a predefined format or schema.

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PDF data type

A file format used to present documents, including text and images, independently of application software, hardware, and operating systems. Considered to be unstructured data.

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Statistical test for mean rating difference (independent samples)

A t-test is used to determine if there's a statistically significant difference in the average ratings between two groups (hotels) when the groups are independent.

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Measurement scale for movie genre

Movie genre is a nominal scale; it categorizes things into named groups without a meaningful order.

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Measurement scale for release date

A release date is measured on an interval scale; it's numerical and has meaningful order but lacks a true zero point.

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Measurement scale for total gross

Total gross earnings (box office revenue) is a ratio measurement – it has a true zero point and meaningful ratios.

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Measurement scale for MPAA rating

MPAA ratings (e.g., G, PG, PG-13, R, N-17) are ordinal; they have a meaningful order but not a true zero, and intervals aren't equally spaced.

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Insignificant variable in regression analysis

An insignificant variable in a regression at a given significance level (e.g., 95%) means its coefficient doesn't have a statistically meaningful relationship to the dependent variable.

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Independent samples

Independent samples are data points that are not related to each another; each data point is from a separate group, without any connection between the two groups.

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Concept of significance level in regression

Significance level (e.g., 95%) sets the threshold for determining if a variable's contribution to a regression model is statistically meaningful; values above this are considered significant; values below are insignificant.

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Data Preparation for Missing Age

Process of handling missing data in the 'age' column of an employee dataset.

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Imputation using K-NN

Method of filling missing values in a dataset by finding the nearest neighbours.

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Imputation using Mean

Method to fill missing values by using the average value of a column.

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Eliminating Records (Missing Values)

Removing rows with missing values from the dataset.

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New Category for Missing Values

Creating a new category or label for missing values.

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Statistical Significance

A measure of whether observed differences between groups are likely due to chance.

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Gross Reproduction Rate

The average number of daughters a woman would have in her lifetime.

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Total Fertility Rate

Average number of children a woman of childbearing age would have in their lifetime.

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Certificate of Entitlement (COE)

A document granting the right to own and operate a vehicle in Singapore.

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Vehicle Quota

The limited number of COEs available in specific categories.

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Data Issue

A problem or flaw in a dataset that affects its accuracy or reliability.

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Predictive Model

A model that is trained to forecast future outcomes based on historical data.

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Outcome Variable

The variable in a dataset that represents the result or effect you're trying to predict.

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Input Selection

The process of choosing which variables will be used in a model to determine the outcome.

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Heat Map

A visualisation that uses colours to represent different values of variables in a dataset.

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Mode of Shipping

The preferred method of transportation for goods or items.

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Website traffic

The number of visitors to a website, typically measured over a specific time period like a month.

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Advertisements

Paid promotions displayed on various platforms (TV, websites, etc.) to reach potential customers.

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Correlation

A statistical relationship between two or more variables, indicating whether they tend to change together.

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Missing data

Data points that are absent or incomplete in a dataset.

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Data cleaning

The process of identifying and correcting errors or inconsistencies in a dataset to improve its quality.

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Mean value

The average of a set of numbers, calculated by summing all the values and dividing by the total number of values.

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Merge datasets

Combining data from two or more datasets into a single dataset, often based on shared columns or keys.

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Replace missing data

Substituting missing data points with reasonable values based on the context and data patterns.

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Compare Sales by Category and Region

Create a visualization to compare sales (product of selling price * quantity, summed across all orders) by product category and region. This helps understand sales performance across different areas for informed marketing strategies.

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Product Category Proportion by Region

Visualize the proportion of each product category bought by companies in various regions, based on the quantity sold. This helps analyze regional buying preferences.

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Selling Price by Region and Customer Segment

Investigate the selling price variation across regions and customer segments. This analysis helps identify pricing strategies and understand customer segment-specific pricing behavior.

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Superstore Dataset

This dataset contains information about sales transactions of a fictional company called Superstore. It includes details like product categories, regions, customer segments, and sales data.

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Data Visualization Tools

These tools, like Python libraries (e.g., matplotlib, seaborn) or software like Tableau, are used to create visual representations of data to gain insights and make data-driven decisions.

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Study Notes

Neo Teng Yong STU-SIT Quiz Notes

  • Attempt 4: Submission date: April 14, 2022, 12:15-12:16 PM.

  • Question 1: Customers rated AA and BB hotels independently. A T-test should be used to check for statistically significant difference in mean ratings between the two hotels.

  • Question 1 Data:

    • AA hotel: 7, 6, 6, 10, 6, 6, 10, 1, 6, 5, 4, 10, 10, 1, 6, 6,10, 1, 8, 6
    • BB hotel: 8, 10, 6, 5, 10, 3,4, 9,

  • Question 2: Movie title, Release date, Genre, MPAA rating, and Total Gross.

  • Question 2 Data: Film data.

  • Question 3: Fitness Index is the dependent variable.

  • Question 3 Data: Coefficient, Standard Error, t Stat, P-value of age, sleep quality, pulse rate, and female.

  • Question 3 Results: Identify insignificant variables at a 95% significance level.

  • Question 4: Suggest the appropriate data visualisation technique for analyzing total government expenditure on education.

  • Question 4 Data: Total expenditure on education data by year.

  • Question 4 Results: Line chart would be suitable.

  • Question 5: Which variable should not be included in a statistical predictive model with outcome variable "Turnover"?

  • Question 5 Data: Variable Name, Role, Measurement Level, Description

  • Question 5 Results: Age should not be included.

  • Question 6: Which regression model should be chosen based on adjusted R-squared values?

  • Question 6 Data: Model C: Adjusted R-square = 0.68; Model B: Adjusted R-square = 0.88; Model D: Adjusted R-square = 0.26; Model A: Adjusted R-square = 0.79

  • Question 6 Results: Model B with highest adjusted R-squared.

  • Question 7: Appropriate statistical techniques for finding effect sizes of various factors on sales growth rate.

  • Question 7 Results: Logistic regression, decision tree, Neural Network Analysis, and Linear Regression are all potential techniques.

  • Question 8: Determine the validity of statements about the scatterplot of two variables.

  • Question 8 Data: Plot analysis.

  • Question 8 Results: Y's variability is unequal across X's range, there is positive linear correlation between x and y.

  • Question 9: Appropriate techniques for detecting tumor cells in x-ray images.

  • Question 9 Results: Decision Tree, Support Vector Machines, Neural Network, and Linear Regression.

  • Question 10: Data classification type.

  • Question 10 Data: Data types, PDF File

  • Question 10 Results: PDF format data would be classified as structured repetitive

  • Question 11: N/A.

  • Question 12: Data preparation steps for missing age values in employee data.

  • Question 12 Results: Eliminating records with missing values or imputing missing values using K-NN or the mean are possible solutions.

  • Question 13: No data for analysis is presented

  • Question 14: No data for analysis is presented

  • Question 15: Data issues with the input selection for the study. (No details provided)

  • Question 16: No data for analysis is presented

  • Question 17: Evaluation of suitability of datasets for analysis. (No details provided)

  • Question 18: Data preparation steps for predictive modeling for accident severity. (No details provided)

  • Question 19: No data for analysis is presented.

  • Question 20: Data cleaning steps for two datasets (Sales and Town). (No details provided)

  • Question 21: No data for analysis is presented.

  • Question 22: Creating visualizations for sales comparison by category and region, comparing product category purchases by region, and analyzing selling prices by region and customer segments. (No details provided)

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Description

This quiz covers statistical analysis techniques using real data, including T-tests for comparing hotel ratings and regression analysis for understanding fitness indices. It also explores data visualization methods for government expenditure analysis. Test your knowledge of these important statistical concepts and practices.

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