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Data Analysis for Business and Finance
Rating: 3.8 out of 5(136 ratings)
21,667 students

Data Analysis for Business and Finance

Learn Data Analysis: Descriptive & Inferential Statistics, Regression Analysis, Time Series and much more!
Created bySaurav Singla
Last updated 9/2020
English

What you'll learn

  • Understand Statistics from basic to advance level
  • Learn Descriptive and Inferential Statistics
  • How to plot different types of data
  • Exploratory data analysis: graphical and numerical approaches (Mean, Mode, Standard Deviation etc)
  • Exploring data analysis: Univariate and Bivariate Analysis
  • Calculate Covariance and Correlation
  • Understand the Central Limit Theorem
  • Understand standard deviations
  • Probability: Essentials and Conditional Probability
  • Distinguish and work with different types of Probability Distributions (advance level distributions covered extensively)
  • Calculate the measures of Central Tendency, Asymmetry, and Variability
  • Understand what a Sampling and Estimation is
  • Statistical Inference: Perform Hypothesis testing and Estimate Confidence Interval (from basics to deep dive)
  • Regression Analysis and estimating relationships among variables (including complex level of testing with F-statistics and T-tests)
  • Time-Series: Simple/Linear/Moving Average/Exponential, Smoothing techniques, Seasonality, Decomposition methods
  • Make data driven decisions using the above (covering examples)

Course content

1 section • 11 lectures • 4h 34m total length

  • Uni-variate Variable Analysis -130:29

    You will learn techniques on exploratory data analysis using mean, median, mode, minimum, maximum, percentiles, quartiles, range, IQR, variance, standard deviation.

  • Uni-variate Variable Analysis - 223:40

    You will learn techniques on exploratory data analysis using MAD, skewness, kurtosis, histogram, boxplot, line chart, pie chart, bar chart, scatterplot, outliers, table of summary, missing values.

  • Bi-variate Variable Analysis18:40

    You will find a relationship between the variables using a crosstab, chi-square test, ANCOVA, scatterplot, correlation, covariance, boxplot.

  • Probability20:07

    In this lecture, you will learn on probability, addition rule, multiplication rule, conditional probability, probabilistic independence, equal likely events, discrete and continuous random variables, mean, variance, standard deviation, conditional mean and variance.

  • Probability Distributions39:01

    You will learn different distributions such as normal distribution, continuous distributions, density function, z value, binomial distribution, poisson distribution, exponential distribution, triangular distribution, bernoulli distribution, chi-square distribution, beta distribution, weibull distribution.

  • Sampling and Sampling Distributions24:23

    You will learn different sampling techniques such as random sampling, systematic sampling, stratified sampling, cluster sampling. You will learn about the sample, population, sampling frame, point estimate, sampling distribution, confidence interval, unbiased estimate, standard error of the estimate.

  • Statistical inference: Hypothesis Testing29:42

    In this lecture, you will learn on null and alternative hypothesis, one tail and two-tail tests, type 1 and type 2 errors, significance level and rejection region, p-value, confidence interval, the population mean population proportion, differences between population means, equal population variances, differences between population proportions, chi-square goodness of fit test, lilliefors test, quantile-quantile (Q-Q) plot, chi-square test for independence.

  • Statistical inference: Confidence Interval17:41

    You will learn on the confidence interval, z value,  t distribution, chi-square & F distributions, mean, population total, population proportion, standard deviation, the difference between means, independent samples, equal variance, paired sample, the difference between proportion, sample size selection.

  • Regression Analysis23:42

    You will learn on regression analysis, scatterplot, outlier, unequal variance, least-square estimation, standard error of estimate, dummy variables, R2, adjusted R2, Logarithmic transformations.

  • Regression Analysis - Statistical Inference18:35

    You will learn on assumptions of the regression model and determining which explanatory variables belong in the regression equation.

  • Time Series28:11

    You will learn the forecast error, run test, autocorrelation, linear trend model, exponent trend model, random walk model, moving average, simple exponent smoothing, holt model, seasonal model, deseasonalizing.

  • Statistics
  • Time Series

Requirements

  • No prior knowledge or experience is required. We start from the basics and gradually build up your knowledge and skills.

Description

In these volatile and continuously evolving times, there’s no dearth of data available from multiple sources. Therefore, it becomes imperative that such data is validated and converted into meaningful information that can be used to make optimal decisions.

This course exactly focuses on this and exposes you to various tools and methods that can be used to interpret data and derive information. What you learn in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success within your organization.

If you are aiming for a career as a Data Scientist or Data Analyst then lay foundation on your Statistics, Regression, Time Series skills are a few things you wish to try and do. It covers the essentials of descriptive, predictive, and prescriptive analytics. It focuses on problem-solving by model development and solution interpretation. Use appropriate Data Analysis techniques for real-world problems and data. Write comprehensive and critical reports evaluating and interpreting obtained results.

So many courses and books just bombard you with the theory, and math, and coding... But they forget to explain, perhaps, the most important part: why you are doing, what you are doing. And that is how this course is so different. We focus on developing an intuitive feel for the concepts behind Data Analysis.

With our intuition tutorials, you will be confident that you understand all the techniques on an instinctive level. This is a game-changer for both business managers and finance professionals who can now learn techniques to maximize their knowledge and skills.

In conclusion, this is an exciting training program filled with intuition tutorials and techniques that can be applied to all sets of data to make decisions that can benefit you in both personal and professional life.

We are super enthusiastic about Data Analysis and hope to see you inside the class!

Saurav Singla

Who this course is for:

  • Financial/Business analysts
  • People who want a career in Data Science
  • People who want a career in Business Intelligence
  • People who want a career in Data Analytics
  • Business executives
  • Individuals who are passionate about numbers and quant analysis
  • Anyone who wants to learn the subtleties of Statistics and how it is used in the business world
  • People who want to start learning statistics
  • People who want to learn the fundamentals of statistics

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