SkillSoft Explore Course – Lambers, Inc.

Aspire Business Analyst to Data Analyst Business Analyst to Data Analyst - Track 1: Business Analyst

Excel's Scenario Manager allows you to create named scenarios with different values for key variables. These scenarios can be quickly examined and summarized using the What-If Analysis tool.

In this course, you'll use GoalSeek and Solver, both of which are mathematical tools. Goal Seek comes in handy when solving quadratic, cubic, or other equations. Solver is much more powerful and allows complex constrained optimization problems to be easily defined and addressed.

As you'll recognize, Solver's interface, used for specifying objective functions and constraints, is intuitive and easy to use.

Next, you'll use several heavy-duty statistical techniques in Analysis ToolPak. These range from the creation of correlation and covariance matrices, hypothesis testing, and F-test and T-test interpretations to ANOVA, random and periodic sampling, and the construction and analysis of linear regression models.

Asset ID	it_dacgexdj_06_enus
Course Type	Video Course
Course Category	Business Analyst to Data Analyst

Objectives
Complete Guide to Excel 365: What-If Analysis, Solver, & Analysis ToolPak discover the key concepts covered in this course Use the What-If Analysis feature in Excel, create scenarios based on specific cell values, assign names to these scenarios, and toggle between them, summarize a range of outcomes across scenarios by performing What-If Analysis, and interpret the returned results Â use Goal Seek for solving simple univariate optimization problems, such as solving univariate equations where a target output cell must be set to a specific value by changing a single input cell enable the Solver add-in and use it to perform complex multi-variable optimization, specify objective functions to min/max or specific values, and specify non-negativity conditions and solution methods for contraints perform simple statistical analysis of two-dimensional data, compute measures of central tendency (mean, median, mode) and dispersion (standard deviation and variance), define Bessel's correction, and calculate skew and kurtosis Â enable Analysis ToolPak and use it to compute correlation and covariance matrices, interpret the results, and recognize the link between covariance and variance implement hypothesis testing using the Analysis ToolPak, perform the two-sample F-test for variance equality and two-sample t-test for equality of means, and interpret the significance level (alpha), test statistic, and p-value implement ANOVA (Analysis of Variance) using Analysis ToolPak to analyze variances within and between groups Â use Analysis ToolPak for histogram analysis and descriptive statistic computing, compute ranks and percentiles, and perform both random and periodic sampling Â generate random numbers drawn from various distributions using Analysis ToolPak,Â applyÂ normal, Bernoulli, Poisson, and other distributions, specify population parameters, such as mean and variance, and recognize why sample mean and variance might differ from them Â perform linear regression using Analysis ToolPak, interpret the results of regression including R-square, p-values, and t-statistics of individual regression coefficients, and identify the benefits of using Analysis ToolPak over worksheet functions such as LINEST(),SLOPE(), and INTERCEPT() Â summarize the key concepts covered in this course

Objectives

Complete Guide to Excel 365: What-If Analysis, Solver, & Analysis ToolPak

discover the key concepts covered in this course
Use the What-If Analysis feature in Excel, create scenarios based on specific cell values, assign names to these scenarios, and toggle between them, summarize a range of outcomes across scenarios by performing What-If Analysis, and interpret the returned results Â
use Goal Seek for solving simple univariate optimization problems, such as solving univariate equations where a target output cell must be set to a specific value by changing a single input cell
enable the Solver add-in and use it to perform complex multi-variable optimization, specify objective functions to min/max or specific values, and specify non-negativity conditions and solution methods for contraints
perform simple statistical analysis of two-dimensional data, compute measures of central tendency (mean, median, mode) and dispersion (standard deviation and variance), define Bessel's correction, and calculate skew and kurtosis Â
enable Analysis ToolPak and use it to compute correlation and covariance matrices, interpret the results, and recognize the link between covariance and variance
implement hypothesis testing using the Analysis ToolPak, perform the two-sample F-test for variance equality and two-sample t-test for equality of means, and interpret the significance level (alpha), test statistic, and p-value
implement ANOVA (Analysis of Variance) using Analysis ToolPak to analyze variances within and between groups Â
use Analysis ToolPak for histogram analysis and descriptive statistic computing, compute ranks and percentiles, and perform both random and periodic sampling Â
generate random numbers drawn from various distributions using Analysis ToolPak,Â applyÂ normal, Bernoulli, Poisson, and other distributions, specify population parameters, such as mean and variance, and recognize why sample mean and variance might differ from them Â
perform linear regression using Analysis ToolPak, interpret the results of regression including R-square, p-values, and t-statistics of individual regression coefficients, and identify the benefits of using Analysis ToolPak over worksheet functions such as LINEST(),SLOPE(), and INTERCEPT() Â
summarize the key concepts covered in this course