5.2.3.8 Lab - Visualizing Data in Excel (Instructor Version) Objectives Part 1: Prepare Data for Visualization Install the analysis ToolPak. Create random numbers. Export a CSV file. Part 2: Create Excel Charts for Visualizing Data Create a frequency distribution. Create and customize a column chart Create a scatter …
4.3.2.4 Lab - Internet Meter Anomaly Detection (Instructor Version) Objectives Part 1: Feature Engineering Part 2: Euclidean Anomaly Detection Scenario/Background Anomaly-detection algorithms locate those datapoints that stand out from a pattern. For example, algorithms of this kind can be used to test the safety of airplane engines by …
4.3.1.4 Lab - Internet Meter Linear Regression (Instructor Version) Objectives In this lab, you will become familiar with the concepts of regression and prediction and the concept of working with data. Part 1: Import the Libraries Part 2: Visualize the Historical Data Part 3: Create a Simple Linear …
4.2.2.5 Lab - Evaluating Fit Errors in Linear Regression (Instructor Version) Objectives In this lab, you will become familiar with the concepts of evaluating fit errors in linear regression. Part 1: Import the Libraries and Data Part 2: Calculate the Errors Scenario / Background In statistics, linear regression …
4.1.3.5 Lab - Decision Tree Classification (Instructor Version) Objectives In this lab, you will use a decision tree classifier model to determine who survived the Titanic cruise ship disaster. Part 1: Create a Decision Tree Classifier Part 2: Apply the Decison Tree Model Part 3: Evaluate the Decison …
4.1.2.4 Lab - Simple Linear Regression in Python (Instructor Version) Objectives In this lab, you will become familiar with the concepts of simple linear regression and working with the provided data to make a prediction. Part 1: Import the Libraries and Data Part 2: Plot the Data Part …
3.2.1.6 Lab - Internet Meter Visualization (Instructor Version) Objectives Part 1: Clean and Analyze Data Part 2: Visualize Data Scenario/Background In this lab, you will learn how to use the pandas library to perform the preliminary steps that are needed before perfoming any data analysis. This includes removing …
3.1.5.5 Lab - Correlation Analysis in Python (Instructor Version) Objectives Part 1: The Dataset Part 2: Scatterplot Graphs and Correlatable Variables Part 3: Calculating Correlation with Python Part 4: Visualizing Scenario/Background Correlation is an important statistical relationship that can indicate whether the variable values are linearly related. In …
3.1.4.6 Lab - Descriptive Statistics in Python (Instructor Version) Objectives Part 1: Analyzing the Data Part 2: Visualizing the Data Scenario/Background In this lab, you will import a data set into a pandas frame and generate descriptive statistics from the data. You will format text strings report the …
2.5.2.5 Lab - Internet Meter SQL (Instructor Version) Objectives Part 1: Set up your Database Part 2: Connect to the Database Part 3: Manipulate the Data with Pandas Part 4: Join Tables with Pandas </b> Scenario/Background In this lab you will learn how to connect to a relational …
