
Engage in exploratory data analysis to build a foundation for business intelligence, spot data issues and anomalies, and identify variables using graphical and non-graphical methods, including univariate and multivariate approaches.
Explore descriptive analysis by using mean, median, and mode to describe data, visualize distribution with histograms, and assess spread with variance and standard deviation.
Predictive analysis uses data mining, modeling, and statistics to forecast future events and uncover patterns and trends, with visualizations and real-time information.
Distinguish categorical (nominal and ordinal) from numerical (continuous and discrete) data; summarize with frequencies and proportions, and visualize categories with bar or pie charts, numerical data with box plots.
Analyze categorical data with pivot tables in Excel to reveal how job role and salary influence upgrade decisions, using nominal and ordinal data to explore demographics.
Use countif in Excel to count the frequency of two-dice sums and divide by the 36-outcome sample space to obtain probability, illustrating higher chances for sums like seven.
Learn to build a joint probability pivot table in Excel to analyze single event probability, joint probability, mutually exclusive and not mutually exclusive events, and conditional probability.
Explore the normal distribution, its bell-shaped curve, and symmetry, noting mean, median, and mode equivalence. Understand standard deviation and the 68-95-99.7 rule for data spread.
Explore how confidence intervals quantify the reliability of estimates in business statistics. Understand how the confidence level and alpha relate to the probability that the interval contains the true value.
Calculate confidence intervals in Excel using confidence.norm and confidence.t with a 25-stock sample over five years. Determine the mean, standard deviation, and alpha to obtain upper and lower limits.
Learn to calculate the sample size needed to estimate a population mean with 95% confidence within 25 kilometers, using sigma 40.25 and z 1.96, rounding up to 10.
Perform a z-test in Excel to test if the mean debtor days is less than 29, using known population standard deviation 2 and alpha 0.05, and interpret the p-value.
Explore Power BI Desktop to get data from multiple sources, from files and SharePoint to online services and databases, using Power Query, and model data with measures, columns, and relationships.
This course is an introduction level course to business and data analytics. The aim is to address several competencies, Data awareness, statistical applications in excel, business intelligence software and machine learning awareness.
The first competency is data trend awareness. What are the different fields? What are the different analysis types and tool? and what are the general buzz terms? By the end of this section you should have an advanced level of awareness on the types of data, the role of a data scientist and the types of.
After this we ill look at Statistical application in Excel. By the end of this you should have the ability to carry out an interpenetrate the results from Descriptive Statistics, calculate probability and select samples and variables, Understand the power of hypothesis testing to solve business problems all within Excel
We will then move into power bi, and self-service tool for business intelligence. You will learn how do to simple transformations on data, how to model data using DAX and how to visualize data
When discussing data and business analytics you can not overlook machine learning. By the end of this course you will have an advanced level of awareness on how this works and where it can be applied.
By the end of this course you should feel comfortable Implementing business intelligence solutions to your organisation using tools such as Excel or Power BI that improve the current reporting system and add greater depth to the information to aid in the business decision making process.
Although this course only has 5 hours or so of video material, the reality is you should expect to take about 20 hours to really complete the course and gain full understanding. There are many activities to complete and it might be necessary to revisit tutorials to ensure you gained the knowledge that you want.