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Salary prediction for data business analysis
- 1. Data Analyst Salary Prediction Project April2022 Maria Gallardo Higher Diploma in Science in Data Analytics
- 2. Agenda 1. Introduction 2. WorkRelated 3. Methodology 4. Results 5. Conclusions 6. Q&A
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- 4. Help jobs seekersto source Data Analyst jobs based on income more effectively Exploratory Analysis Machine Learning techniques Tableau Dashboard
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- 6. Literature Review 1. SalaryPrediction in the IT Job Market with Few High-Dimensional Samples: A Spanish Case Study 2. Faculty salary as a predictor of student outgoing salaries from MBA programs Appeal to the human condition 3. Benchmarking regression algorithms for income prediction modeling,
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- 10. Pre-processing Data •Removal unnecessary variables • Salary and Stare column split • Cleaned unnecessary characters & punctuation • Cleaned noisy values (-1) • NA values replaced by mean or mode Data distribution minsalary Distribution by sector
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- 12. Exploratory Data Analysis WhatState is hiring most? What are the most common titles? Number of jobs by State Most common job titles Remote R
- 13. Exploratory Data Analysis Whatare the most frequent words in descriptions? What are the most common programming language?
- 14. Exploratory DataAnalysis What arethe sectors/industries better paid? ANOVA H0 = thereis no difference amongmeans. Ha = at least one group differs significantlyfrom the overall mean of averagesalary. α = 0.05 Sector: F(24,5606) = 1.2, p > 0.05 Industry: F(103,5527) = 1.367, p < 0.05
- 15. Exploratory DataAnalysis What aretheStates better paid? ANOVA H0 = thereis no difference amongmeans. Ha = at least one group differs significantlyfrom the overall mean of averagesalary. α = 0.05 F(39,5591)= 34.84, p < 0.05 Post HocTest CA-AZ,p < 0.05 OR-AZ, p < 0.05 UT-AZ, p < 0.05
- 16. Exploratory DataAnalysis Are RatingandSalary correlated? Shapiro-WilkTest H0 = dataare normallydistributed. Ha = is that dataare not normallydistributed. α = 0.05 F(39,5591)= 34.84, p < 0.05 Results: AverageSalary: p-value < 2.2e-16 Rating: p-value< 2.2e-16
- 17. Machine Learning Clustering –K-Means Variables: Avg.Salary Type ownership Rating Clusters K = 3 Accuracy 0 %
- 18. Machine Learning Lineal Regression Results: Median& mean are zero Residual standarderror = $19,170 Max salary= $150,000 MultipleR-squared= 84% Hypothesis: (H0) = dependent variable and independent variable(s) haveno relationship HA = dependent variable and independent variable(s) haverelationship α = 0.05 F(1.5,4422)= 6.337e-16, p < 0.05
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- 21. Data Analyst Senior DataAnalyst Junior Data Analyst Business Data Analyst Professionals % of total Conclusions Top Salary States Most common titles Skills Data Analyst in USA • Oregon • Washington • California Top Salary Industries • Media & Entertainment Retail Stores • Health Fundraising • Beauty & Personal accessories Linear Regression Rating, size, type of ownership, industry, revenue, company, sector , revenue, state and job title predicts salary average. • 84 % • There is relashionship between the dependants and independant variables
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