Week 09-10, Online Discussion Forum: Textbook 2, Data Strategy – Chapter(s) 3 – 4 Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things by Bernard Marr – Paperback – April 28, 2017 ISBN-10: 9780749479855 – ISBN-13: 978-0749479855 . Please read the following chapter(s) from our Textbook 2 – Data Strategy: […]
Discipline: Analytics
To predict the price by performing predictive analysis using the Regression technique in Excel.To predict the price by performing predictive analysis using the Regression technique in Excel.
To review the assignment, look at the attachments. Walk me through all the steps in Excel (Word or PDF format) For example, Data > Data Analysis > Regression > OK and so on (shortly step by step). Just write down what you did.
Generate frequency distribution, relative frequency distribution, and percent frequency distribution of columnGenerate frequency distribution, relative frequency distribution, and percent frequency distribution of column
Question 1: Generate frequency distribution, relative frequency distribution, and percent frequency distribution of column Position on Automobile. Question 2: Generate frequency, cumulative frequency, cumulative relative frequency, and cumulative percent frequency of column Tread Depth? Use bin (0 – 3], (3-6], (6-9], (9-12] Question 3: ( assigment 2 Use the formulas provided in the lecture notes to fill […]
data mining goals analytical types as well as writing the constraints and objectives in terms of decision variablesdata mining goals analytical types as well as writing the constraints and objectives in terms of decision variables
Question 1 Four business case scenarios are given below. Please summarize their data mining goals according to the background, customer needs, and business objectives. Indicate the analytical types that should be used for each data mining goal. Case 1 · Background: A prestigious university aims to improve its admissions process. Their goal is to attract high-caliber students and ensure a […]
Wk 5 Discussion: Statistical Models and Visualizing Information [due Thurs] Wk 5 Discussion: Statistical Models and Visualizing InformationWk 5 Discussion: Statistical Models and Visualizing Information [due Thurs] Wk 5 Discussion: Statistical Models and Visualizing Information
Statistical models help us describe and summarize relationships between variables. Understanding how process variables relate to each other helps businesses predict and improve performance. A marketing manager wants to understand the relationship between advertising and sales. When a new advertising campaign rolls out, they will look at the impact on total sales to determine if it is […]
Discuss how benchmarking relates to an effective management operating system and how SOPs can be used to ensure performance measurements support operational excellence.Discuss how benchmarking relates to an effective management operating system and how SOPs can be used to ensure performance measurements support operational excellence.
There are four links to the related instructional videos; please see the attachment. Benchmarking is a management accounting innovation (MAI) that can be used for performance measurement and management in both the private and the public sectors. Discuss how benchmarking relates to an effective management operating system and how SOPs can be used to ensure performance […]
MARK 2034: Marketing Analytics SP4-2024 Assessment 2 – Technical Analysis (Part A)MARK 2034: Marketing Analytics SP4-2024 Assessment 2 – Technical Analysis (Part A)
In this assessment, you take on the role of a Market Analyst to analyse marketing data for two different clients. You will be using tools and techniques that are commonly used in the marketing industry to analyse brand performance and product structures. Individually, you will be required to complete technical analysis using two separate datasets […]
Investigating Driver Behavior Effects on Usage-Based Car Insurance focusing on accident predictionInvestigating Driver Behavior Effects on Usage-Based Car Insurance focusing on accident prediction
4. Introduction – Chapter One Background information Definition and brief elaboration of key concepts Identification of main developments in the study area and any gaps Brief conceptualization of the study (context, trends) Problem Statement Background of the problem backed by literature Clear statement of the problem Research gap identified Linking of problem statement to study […]
explain the application of the CRISP-DM Model in Data Mining. Provide a practical example where you can apply the model for data mining.explain the application of the CRISP-DM Model in Data Mining. Provide a practical example where you can apply the model for data mining.
Data mining and analytics lifecycle are designed for big data problems. Data mining and analytics follow best practices for the successful completion of big data mining projects. CRISP-DM is a popular approach for data mining projects. In this discussion board, explain the application of the CRISP-DM Model in Data Mining. Provide a practical example where […]
W6: Hypothesis testing I and II; Testing differences between means, variances and proportionsW6: Hypothesis testing I and II; Testing differences between means, variances and proportions
A town official claims that the average vehicle in their area sells for more than the 40th percentile of your data set. Using the data, you obtained in week 1, as well as the summary statistics you found for the original data set (excluding the super car outlier), run a hypothesis test to determine if the claim can […]