Microsoft Excel For A-Z Data Analysis Statistics & Dashboard

Unleash Excel for Complete Data Analysis. Master Important Functions, PivotTables, Analysis Tools, Graphs and Dashboard.

What you'll learn

You will learn to clean and format data, including removing duplicates, handling missing data, and managing outliers to ensure data integrity.

You will learn advanced techniques for sorting and filtering data to efficiently extract relevant insights from large datasets.

You will learn how to apply conditional formatting in Excel to visually highlight key trends, insights, and anomalies within your data.

You will learn essential Excel formulas and functions such as SUM, AVERAGE, COUNT, IF statements and MORE, enabling you to manipulate data effectively.

You will learn to utilize Excel's lookup functions (VLOOKUP, HLOOKUP, XLOOKUP) to efficiently search for and retrieve specific information within datasets.

You will learn various graph and chart types in Excel for data visualization, including bar charts, pie charts, scatter plots, and more to communicate insights.

You will learn advanced analysis using PivotTables and PivotCharts, enabling you to analyze, and visualize complex datasets with ease and interactivity.

You will learn to use Excel's built-in data analysis tools for statistical analysis, i.e., descriptive statistics, t-tests, ANOVA, correlation, and regression.

You will learn to design and create dynamic DASHBOARD in Excel, by a visually interactive format for effective decision-making and reporting.

You will learn best practices for enhancing your Excel dashboard, including layout optimization, graphical elements, etc., to maximize impact and usability.

Requirements

Microsoft Excel Installed

Desktop/Laptop (Mac or Windows)

Dedication to learn

Description

Unlock the power of data analysis with Excel in this comprehensive course designed to take you from novice to proficient data analyst. Whether you're new to Excel or looking to expand your skills, this course equips you with the essential tools and techniques to excel in data analysis.Throughout the course, you'll dive deep into data cleaning and formatting, learning how to remove duplicates, handle missing data, and manage outliers effectively. You'll discover advanced sorting and filtering methods to extract valuable insights from complex datasets, and you'll master conditional formatting to visually highlight trends and anomalies.With a focus on practicality, you'll gain proficiency in essential Excel formulas and functions for calculations, date manipulation, and conditional operations. You'll also harness the power of lookup functions to quickly retrieve specific information, streamlining your analysis workflow.Data visualization is a key component of effective analysis, and you'll learn to create a variety of graphs and charts in Excel to communicate insights with clarity. From bar charts to scatter plots, you'll explore different visualization techniques to enhance data interpretation and presentation.PivotTables and PivotCharts offer dynamic ways to summarize and analyze data, and you'll learn how to leverage these tools for advanced analysis and visualization. Additionally, you'll delve into Excel's statistical analysis tools, performing tasks such as descriptive statistics, t-tests, correlation, and regression analysis.As you progress, you'll bring your newfound skills together to create dynamic dashboards in Excel, consolidating information into visually appealing and interactive formats for effective decision-making and reporting. You'll refine your dashboard with layout optimization and graphical elements, ensuring maximum impact and usability.By the end of this course, you'll emerge as a proficient Excel user, equipped with the knowledge and skills to tackle data analysis challenges confidently and efficiently. Whether you're a professional seeking to enhance your career prospects or a student aiming to develop practical Excel expertise, this course empowers you to master data analysis from zero to hero.

Overview

Section 1: Don't Ignore It. Start From Here!

Lecture 1 Instructions you MUST follow

Lecture 2 Excel functions and shortcuts cheatsheet

Section 2: Necessary Foundation of Data Analysis

Lecture 3 What is data analysis?

Lecture 4 Key components of data analysis

Lecture 5 Understanding exploratory data analysis

Lecture 6 Methods of exploratory data analysis Part 1

Lecture 7 Methods of exploratory data analysis Part 2

Lecture 8 Methods of exploratory data analysis Part 3

Section 3: Necessary Foundation of Statistical Analysis

Lecture 9 What is statistical data analysis?

Lecture 10 Statistical data analysis v/s EDA

Lecture 11 Population v/s sample and its methods

Lecture 12 Types of statistical data analysis

Lecture 13 A recap on descriptive analysis

Lecture 14 Inferential statistics Part 1 – T-tests and ANOVA

Lecture 15 Inferential statistics Part 2 – Relationships measures

Lecture 16 Inferential statistics Part 3 – Linear regression

Section 4: Necessary Foundation on Hypothesis Testing

Lecture 17 Hypothesis testing for inferential statistics

Lecture 18 Selecting statistical test and assumption testing

Lecture 19 Confidence level, significance level, p-value

Lecture 20 Making decision and conclusion on findings

Lecture 21 Complete statistical analysis and hypothesis testing

Section 5: Necessary Foundation on Data Visualizations

Lecture 22 Visualizing data for the best insight delivery

Lecture 23 Several methods of data visualization Part 1

Lecture 24 Several methods of data visualization Part 2

Lecture 25 Several methods of data visualization Part 3

Section 6: Data Cleaning and Formatting in Excel

Lecture 26 Identify and remove duplicates

Lecture 27 Dealing with missing values

Lecture 28 Defining and removing outliers

Lecture 29 Dealing with inconsistent values

Lecture 30 Text-to-columns for data separation

Section 7: Sorting and Filtering for Data Precision

Lecture 31 Sorting and filtering data

Lecture 32 Advanced filtering with criteria

Section 8: Conditional Formatting for Tabular Analysis

Lecture 33 Highlighting cells based on conditions

Lecture 34 Findings top and bottom insights

Lecture 35 Creating color scales and color bars

Section 9: Formulas and Functions for Analyzing data

Lecture 36 SUM, AVERAGE, MIN, and MAX functions

Lecture 37 SUMIF, and AVERAGEIF functions

Lecture 38 COUNT, COUNTA, and COUNTIF functions

Lecture 39 YEAR, MONTH and DAY for date manipulation

Section 10: Advanced Formulas and Functions for Analyzing data

Lecture 40 IF STATEMENTs for conditional operation

Lecture 41 VLOOKUP for column-wise insight search

Lecture 42 HLOOKUP for row-wise insight search

Lecture 43 XLOOKUP for robust & complex insight search

Section 11: Graphs and Charts for Data Visualization

Lecture 44 Data analysis with Stacked and cluster bar charts

Lecture 45 Data analysis with Pie chart and line chart

Lecture 46 Data analysis with Area chart and TreeMap

Lecture 47 Data analysis with Boxplot and Histogram

Lecture 48 Data analysis with Scatterplot and Combo chart

Lecture 49 Adjusting and decorating graphs and charts

Section 12: Data Analysis in PivotTables and PivotCharts

Lecture 50 PivotTables for group data analysis PART 1

Lecture 51 PivotTables for crosstab data analysis PART 2

Lecture 52 PivotCharts and Slicers for interactivity

Section 13: Data Analysis Tools for Statistical Analysis

Lecture 53 Descriptive statistics and analysis

Lecture 54 Independent sample t-test

Lecture 55 Paired sample t-test

Lecture 56 Analysis of variance – One way

Lecture 57 Correlation test - relationship measure

Lecture 58 Regression analysis - influence measure

Section 14: Building Dashboard in Excel

Lecture 59 Integrating analysis and graphs for dashboard

Lecture 60 Building a canvas for implementing dashboard

Lecture 61 Creating dashboard with drag and drops

Lecture 62 Final adjustment of dashboard elements

Section 15: Final Project - Data Analysis A-Z in Excel

Lecture 63 Final remark for you

Individuals aiming to develop comprehensive knowledge in data cleaning, analysis, visualization, and dashboard creation in Excel.,Beginners interested in learning practical Excel techniques for efficient data manipulation, visualization, and interpretation.,Professionals seeking to enhance their data analysis skills within the familiar environment of Microsoft Excel.