Learn Data Analysis using Microsoft Excel Basics Fast

Name: Learn Data Analysis using Microsoft Excel Basics Fast
Rating: 1.4 (6 reviews)

Learn Data Analysis using Microsoft Excel

Created byGoh Ming Hui

Last updated 3/2019

English

What you'll learn

Microsoft Excel and Data ANalysis

Course content

1 section • 28 lectures • 40m total length

Getting Started0:49
Start your data analysis journey with Microsoft Excel basics, exploring core ideas and a new feedback option that helps users analyze and organize data.
Downlaod Dataset1:11
Learn to download and work with datasets for statistical analysis in Excel basics, including the iris dataset, and explore high risk datasets to practice data analysis.
Read CSV0:48
Learn how to read csv files in Microsoft Excel to quickly access and analyze datasets. Excel basics support fast data analysis for learners.
Data Mining Process5:37
Understand the data mining process from business understanding with domain experts to data preparation, modeling, evaluation, and deployment, including regression and classification models.
INsert LIne Chart2:54
Insert a line chart in Microsoft Excel and learn to edit the chart, apply borders, and use format options to customize the chart design.
INsert Bar Chart1:33
Create and customize a bar chart in Microsoft Excel by selecting the bar chart type, editing the chart data, and adjusting colors and styles.
INsert Pie CHart1:36
Learn to create and customize a pie chart in Microsoft Excel, including 3d pie charts, borders, and transparency, with basic formatting for clear data.
INsert Scatterplot1:10
Learn how to insert a scatterplot in Excel, perform basic setup steps, and visualize data quickly using essential Excel techniques.
Insert Combo Chart1:07
Learn how to insert and customize a combo chart in Microsoft Excel, format data series, and tailor visuals to clearly compare multiple data types.
Pivot Table3:47
Master pivot tables in Microsoft Excel to analyze data, dragging fields to rows, columns, values, and filters for dynamic insights.
INsert Pivot Table and Pivot CHarts1:23
Master data analysis using Microsoft Excel basics by inserting pivot tables and pivot charts, selecting ranges and fields, and summarizing values for quick insights.
Data ANalysis Plugins0:47
Learn how to enable and use data analysis plugins in Microsoft Excel to perform quick analyses.
Data Analysis PLugin 20:50
Learn to perform data analysis in Microsoft Excel by working with untidy data and preparing the iris dataset for analysis.
Descriptive Statistics1:17
Explore data analysis in Excel and apply descriptive statistics using data analysis tools. Compute means, medians, standard deviations, and confidence intervals to summarize data in the course.
HIstogram1:22
Learn to create a histogram in Microsoft Excel, using frequency and cumulative percentage options to visualize data distributions and adjust settings for the iris data example.
Correlation1:20
Learn to perform correlation in Microsoft Excel using the data analysis tool with iris data as an example, illustrating inferential statistics in data analysis.
Covariance0:53
Explore covariance using Microsoft Excel to analyze iris data and build fundamental data analysis skills.
TTest Two Samples Paired for Means1:31
Explore how to perform a paired two-sample t-test in Excel using data analysis tools, generate p-values and degrees of freedom, and read the t-statistic from the output.
TTest Two Samples Equal Variances1:13
Apply a two-sample t-test with equal variances in Excel to compare mean differences between two variables, understanding degrees of freedom and the t statistic.
TTest Two Samples Unequal Variances1:12
Learn to perform a two-sample t-test for unequal variances in Excel, interpret p-values and degrees of freedom, and compare sample differences.
F Test Two Samples for Variances1:05
Learn to perform an F test for two samples to compare variances in Excel's data analysis tool, interpreting the F statistic, degrees of freedom, and p value.
ANOVA SIngle Factor1:09
Explore how to perform a single-factor anova in Excel using the iris dataset, selecting input ranges and interpreting degrees of freedom and p-values.
ANOVA Two Factor without Replication1:15
Learn to run a two-factor anova without replication in excel, using the iris dataset, and interpret degrees of freedom, mean squares, f statistics, and p values.
Regression Analysis2:03
Explore regression analysis in Microsoft Excel, using the iris dataset to interpret outputs like degrees of freedom, sum of squares, t statistics, p values, and 95 percent confidence intervals.
Remove Duplicates0:47
Learn how to remove duplicates in data preparation with Excel, select a range, and produce clean data by keeping only unique values.
Remove Missing Values1:10
Select a range in Microsoft Excel to remove missing values, then use filtering to identify and delete rows with missing data.
Sort Data0:38
Sort data in microsoft excel by slotting values and organizing columns. Highlight cells, expand selections, and arrange days from largest to smallest for quicker analysis.
Filer Data0:29
Learn to filter data in Excel by using the Data tab, work with columns, and fill in missing values to prepare clean data for analysis.

Requirements

Basic COmputer Knowledge

Description

Why learn Data Analysis and Data Science?

According to SAS, the five reasons are

1. Gain problem solving skills

The ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life.

2. High demand

Data Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase.

3. Analytics is everywhere

Data is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It's a hugely exciting time to start a career in analytics.

4. It's only becoming more important

With the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities.

5. A range of related skills

The great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths. Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise.

The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities.

This is a bite-size course to learn Data Analysis using Microsoft Excel fasts. This course will use CRISP-DM model, and we will go through Data Understanding (Data visualization, Statistics, Data analysis) and Data Preparation (Removing Missing values and removing duplicates) using Microsoft Excel.

You will need to know some computer knowledge before learning this course and you need to know Microsoft Excel before learning also. You can learn Microsoft Excel in my course "Learn Microsoft Excel Basics Fast".

You can take the course as follows and you can take an exam at EMHAcademy to get SVBook Advance Certificate in Microsoft Office and Data Analysis with Excel:

- Learn Microsoft Word Basics Fast

- Learn Microsoft Powerpoint Basics Fast

- Learn Microsoft Excel Basics Fast

- Learn Data analysis using Microsoft Excel Basics Fast.

Content

Getting Started
Download Dataset
Read CSV
Data Mining Process
Insert Lien CHart
Insert Bar Chart
Insert Pie Chart
Insert Scatterplot
Insert Combo Chart
Pivot Table
Insert Pivot Table and Pivot Chart
Data Analysis Plugins
Data Analysis PLugins 2
Descriptive Statistics
Histogram
Correlation
Covariance
TTest Two Samples Paired for means
TTest Two Samples Equal Variances
TTest Two Samples Unequal Variances
F Test Two Samples for Variances
ANOVA Single Factor
ANOVA Two Factor WIthout Replication
Regression Analysis
Remove Duplicates
Remove Missing
Sort Data
Filter Data

Who this course is for:

Beginner Computer Passion People a nd analysts who want to learn Microsoft Excel and Data Analysis