Master Complete Statistics For Computer Science – I

In as we speak’s engineering curriculum, subjects on chance and statistics play a significant function, because the statistical strategies are very useful in analyzing the info and decoding the outcomes.

When an aspiring engineering scholar takes up a mission or analysis work, statistical strategies turn out to be very useful.

Therefore, the usage of a well-structured course on chance and statistics within the curriculum will assist college students perceive the idea in depth, along with getting ready for examinations equivalent to for normal programs or entry-level exams for postgraduate programs.

To be able to cater the wants of the engineering college students, content material of this course, are nicely designed. On this course, all of the sections are nicely organized and introduced in an order because the contents progress from fundamentals to greater degree of statistics.

Consequently, this course is, in truth, scholar pleasant, as I have tried to clarify all of the ideas with appropriate examples earlier than fixing issues.

This 150+ lecture course contains video explanations of every thing from Random Variables, Chance Distribution, Statistical Averages, Correlation, Regression, Attribute Operate, Second Producing Operate and Bounds on Chance, and it contains greater than 90+ examples (with detailed options) that can assist you take a look at your understanding alongside the best way. “Master Complete Statistics For Computer Science – I” is organized into the next sections:

• Introduction
• Discrete Random Variables
• Steady Random Variables
• Cumulative Distribution Operate
• Particular Distribution
• Two – Dimensional Random Variables
• Random Vectors
• Operate of One Random Variable
• One Operate of Two Random Variables
• Two Capabilities of Two Random Variables
• Measures of Central Tendency
• Mathematical Expectations and Moments
• Measures of Dispersion
• Skewness and Kurtosis
• Statistical Averages – Solved Examples
• Anticipated Values of a Two-Dimensional Random Variables
• Linear Correlation
• Correlation Coefficient
• Properties of Correlation Coefficient
• Rank Correlation Coefficient
• Linear Regression
• Equations of the Traces of Regression
• Customary Error of Estimate of Y on X and of X on Y
• Attribute Operate and Second Producing Operate
• Bounds on Possibilities