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Posted at - Feb 16, 2024

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I am looking for a statistician or data analyst who is proficient in Rapidminer. Please get in touch if you have a solid background in data analysing using Rapidminer studio. Following is the task:

Task 2.1) Conduct an exploratory data analysis (EDA) of the salary.csv data set using the

RapidMiner Studio data mining tool. Note this will require use of a number of RapidMiner operators

Provide the following for Task 2.1:

(i) a screen capture of your final EDA process, briefly describe your EDA process

(ii) summarise key results of your exploratory data analysis in Table 2.1 Results of Exploratory Data Analysis for salary.csv.

(iii) Discuss the key results of exploratory data analysis presented in Table 2.1 and provide a rationale for selecting top 5 variables for predicting salary of a person and in particular their relationship with dependent/target variable salary drawing on the results of EDA analysis and relevant literature (About 300 words).

Table 2.1 should include the key characteristics of each variable in the salary.csv data set such as maximum, minimum values, average, standard deviation, most frequent values (mode), missing values and invalid values etc.

Hint: The Statistics Tab and the Chart Tab in RapidMiner Studio provide a lot of descriptive statistical information and the ability to create useful charts like Barcharts, Scatterplots etc for the EDA analysis. You might also like to look at running some correlations and/or chi square tests as appropriate for the salary.csv data set to determine which variables contribute most to predicting house values.

Task 2.2) Build a Linear Regression model for predicting salary of a person using a RapidMiner data mining process and an appropriate set of data mining operators and a reduced set of variables from the salary data set as determined by your exploratory data analysis in Task 2.1. Provide the following for Task 2.2:

(i) A screen capture of Final Linear Regression Model process and briefly describe your Final Linear Regression Model process

(ii) A table named Table 2.2 named Results of Final Linear Regression Model for Task 2.2 for salary data set.

(iii) Discuss the results of the Final Linear Regression Model for salary data set drawing on the key outputs (coefficients, standardised coefficients, t-statistics values, p-values and significance levels etc) for predicting house values and relevant supporting literature on the interpretation of a Linear Regression Model (About 300 words).

Include all appropriate outputs such as RapidMiner Processes, Graphs and Tables that support key aspects of exploratory data analysis and linear regression model analysis of the salary data set in your report.

Note you need export Processes and Graphs from RapidMiner using File/Print/Export Image option and include in Task 2 section where relevant.

My budget is $30.

Please bid if you can do the task in given budget.

Thanks

Task 2.1) Conduct an exploratory data analysis (EDA) of the salary.csv data set using the

RapidMiner Studio data mining tool. Note this will require use of a number of RapidMiner operators

Provide the following for Task 2.1:

(i) a screen capture of your final EDA process, briefly describe your EDA process

(ii) summarise key results of your exploratory data analysis in Table 2.1 Results of Exploratory Data Analysis for salary.csv.

(iii) Discuss the key results of exploratory data analysis presented in Table 2.1 and provide a rationale for selecting top 5 variables for predicting salary of a person and in particular their relationship with dependent/target variable salary drawing on the results of EDA analysis and relevant literature (About 300 words).

Table 2.1 should include the key characteristics of each variable in the salary.csv data set such as maximum, minimum values, average, standard deviation, most frequent values (mode), missing values and invalid values etc.

Hint: The Statistics Tab and the Chart Tab in RapidMiner Studio provide a lot of descriptive statistical information and the ability to create useful charts like Barcharts, Scatterplots etc for the EDA analysis. You might also like to look at running some correlations and/or chi square tests as appropriate for the salary.csv data set to determine which variables contribute most to predicting house values.

Task 2.2) Build a Linear Regression model for predicting salary of a person using a RapidMiner data mining process and an appropriate set of data mining operators and a reduced set of variables from the salary data set as determined by your exploratory data analysis in Task 2.1. Provide the following for Task 2.2:

(i) A screen capture of Final Linear Regression Model process and briefly describe your Final Linear Regression Model process

(ii) A table named Table 2.2 named Results of Final Linear Regression Model for Task 2.2 for salary data set.

(iii) Discuss the results of the Final Linear Regression Model for salary data set drawing on the key outputs (coefficients, standardised coefficients, t-statistics values, p-values and significance levels etc) for predicting house values and relevant supporting literature on the interpretation of a Linear Regression Model (About 300 words).

Include all appropriate outputs such as RapidMiner Processes, Graphs and Tables that support key aspects of exploratory data analysis and linear regression model analysis of the salary data set in your report.

Note you need export Processes and Graphs from RapidMiner using File/Print/Export Image option and include in Task 2 section where relevant.

My budget is $30.

Please bid if you can do the task in given budget.

Thanks

**About the recuiter**Member since Nov 11, 2022 Rattanmehta

from Jalisco, Mexico

**Open for hiring**Apply before - Feb 15, 2025

40 hrs / week

Remote Job

Cost

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