Big Data Analytics Overview

For this assignment, you will come up with a research question and explore it using the techniques of data analysis that we have described in class and explored in the labs. You will develop your own research question and answer that using data from the attached work safety data. You will perform all of the data processing and analysis steps performed using excel or any other software of your choice. Steps you will complete include: Open the attached work safety dataset. Combine and clean data, recode and prepare excel spreadsheets with the variables of interest Change variable names and labels Check for missing data types and variables Code categorical variables in letters or symbols (age group, gender, incident cost, shift) into numerical variables. Compute descriptive statistics (mean, standard deviation, median, minimum, maximum) for incident cost and day lost. Compute frequencies for age group, gender, incident type and shift. Perform histograms of incident cost and day lost. Perform bar graphs and pie chart of age group, gender, incident type and shift. Perform a scatterplot of incident cost (dependent variables) versus day lost (independent variable). Compute a correlation between incident cost and day lost. Perform a simple linear regression analysis between incident cost and day lost. Perform a multiple linear regression between incident cost and day lost, age group, gender, incident type and shift. Interpret the analyses Write-up your findings Components of your analysis Your analysis must include the following and you must interpret the findings. Statistics that exist on their own with no interpretation will not count. 1. Descriptive statistics: 1.1 Show output for and describe descriptive statistics for at least 4 variables 1.2 Show and describe histograms and scatterplots (total of 7 graphics). Histograms with "frequency" on the y-axis are often the most straightforward to interpret. 3. Correlation: Show output for and describe correlations for at the two continuous variables. 4. Regression: 4.1. Complete the bivariate regressions, show output for and describe (coefficients, t- stat, p-value, r-squared) 4.2. Complete the multiple linear regression, show output for and describe (coefficients, t-stat, p-value, r-squared) Note: We do not want to read about all of the intermediary steps that you did, see all of the output you created, hear about syntax errors, things you fixed, etc. Do not include all of your work – only the relevant parts. Requirements: Your assignment includes the following: 1. A narrative of the analysis you conducted, complete with an introduction, Stata output inserted in the body of the text, your interpretations of the output, and a conclusion. Be sure to: Explain your reasoning for including each independent variable, along with your hypothesis for how you thought it would affect the dependent variable (again, you could help to illustrate your reasoning using scatter plots, histograms, or descriptive statistics) Be sure to explain any regression outputs you include clearly, interpreting the r-squared, the coefficients on the independent variables, and the related p- values in plain language. What can you conclude based on your results? Provide a clear conclusion

# Big Data Analytics Overview For this assignment, you will come up with a resea

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