By Prasad Kothari
Explore the large info box and the best way to practice information analytics and predictive modelling in STATA
About This Book
- Visualize and examine facts in STATA to plot a company strategy
- Learn STATA programming and predictive modeling
- Discover how one can develop into a knowledge scientist with the facility of STATA
Who This ebook Is For
This ebook is for all of the pros and scholars who are looking to study STATA programming and follow predictive modelling techniques. This e-book can be very worthy for skilled STATA programmers because it offers complicated statistical modelling thoughts and their application.
What you'll Learn
- Perform vital statistical exams to develop into a STATA information scientist
- Be guided via how one can software in STATA
- Implement logistic and linear regression models
- Visualize and application the information in STATA
- Analyse survey facts, time sequence information, and survival data
- Perform database administration in STATA
In Detail
STATA is an built-in software program package deal that offers you with every little thing you would like for info research, information administration, and pictures. STATA additionally will give you a platform to successfully practice simulation, regression research (linear and a number of) [and customized programming.
This e-book covers info administration, graphs visualization, and programming in STATA. beginning with an creation to STATA and information analytics you will circulation directly to STATA programming and information administration. subsequent, the publication takes you thru facts visualization and the entire very important statistical assessments in STATA. Linear and logistic regression in STATA is usually covered.
As you move in the course of the booklet, you are going to discover a couple of analyses, together with the survey research, time sequence research, and survival research in STATA. you are going to additionally observe varieties of statistical modelling innovations and the way to enforce those recommendations in STATA.
Style and approach
This e-book is a hands-onguide to STATA programming and statistical modelling supplying many STATA code examples and taking. you thru the operating of the code in detail.
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Extra info for Data Analysis with STATA
Sample text
It gives you an advantage in any modeling or visualization exercise. Examining the data Examining the data is always recommended. It is a good idea to examine your data when you first read it into Stata; you should check whether all the variables and observations are present and are in the correct format. While the browse/edit command is used to examine the raw data, the list command is used to see the results of the data. Listing small data is possible through this command. For bigger datasets, options are used to track the data.
3. Select X and Y variable, as shown in the next screenshot: [ 38 ] Chapter 3 4. Click on the Accept button after performing the required changes, as shown in the preceding screenshot. 5. Your output window will open with scatter plot, as shown in the next screenshot: What if you need to add more variables and create complex scatter plots? You can add as many variables as you want and observe the clusters that are naturally available in the scatter plot. Here is a procedure to perform this: 1. Click on the graphing tool again.
In the next chapter, we will talk about the graphical interpretation of the data and the visualization of the data for a better understanding of the data you are handling. [ 36 ] Data Visualization Stata graphics is one of the most important parts that we need to know before we start with modeling. Till now, we have covered basic Stata programs, macros, and data management knowledge and application. This chapter will showcase how to develop different graphs and visualizations in Stata. Here are some of the topics that we will cover in this chapter: • Scatter plots • Line graphs • Histogram/bar charts and other graphs • Statistical calculations in graphs • Curve fitting in Stata graphs Scatter plots Let's start with scatter plots.