Bhargava Mandali
AP Statistics made interactive and concept-focused
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Bhargava Mandali
Bachelors degree
Enroll after the free trial
Each lesson is 55 min
50 lessons
20% off
/ lesson
30 lessons
15% off
/ lesson
20 lessons
10% off
/ lesson
10 lessons
5% off
/ lesson
5 lessons
-
/ lesson
1 lessons
-
/ lesson
Bhargava - About your AP tutor
I have a bachelors in Mathematics and masters degree in Statistics. I have been in the field of teaching for about 15 years including 5 years one-on-one tutoring, and I have tutored 500+ school students on Mathematics and also Statistics for the College Level. I do believe that I have a good understanding of the subject and possess strong analytical skills. I am also efficient in dealing with students studies and making lesson plans according to the need of the Students. I always keep myself updated with the latest teaching methods.
Bhargava graduated from Acharya Nagarjuna University
AP tutor test prep specialities
Homework help
Test prep
Teaching methodology
I offer tutoring sessions on Math and Statistics to high school and university graduates. My tutoring sessions are generally detailed and tailored to the needs of the students. Apart from tutoring, I also help my students with their assignments, homework, and test preparation. I always take regular feedback from my students and parents and also give my feedback on the students performance, so that the tutoring sessions are effective for the learner.
AP concepts taught by Bhargava
The Student and Tutor practiced graphing and solving systems of linear inequalities. They worked through several examples, focusing on shading regions and identifying the solution set. The session concluded with a plan to continue practicing similar problems in a future session to solidify the Student's understanding.
Dotted and Solid Lines
Converting Inequalities to Slope-Intercept Form
Test Points to Verify Solutions
Systems of Linear Inequalities
Shading the Solution Region
Graphing Linear Inequalities
The Tutor and Student reviewed Z-intervals for one and two proportions, covering definitions of confidence intervals, margin of error, and the distinction between population and sample. They practiced interpreting given confidence intervals, calculating point estimates, and evaluating claims based on these intervals. The next session is planned to cover t-intervals and t-tests for small samples.
Population vs. Sample
Confidence Interval Fundamentals
Calculating Point Estimate & Margin of Error
Interpreting Confidence Intervals and Claims
Critical Z-Values for Confidence Levels
The session covered inference for two proportions, including the conditions for the two-proportion Z-interval and the calculation of confidence intervals. The Student practiced applying the formulas, differentiating between sample and population proportions, and using a calculator to find confidence intervals. The Tutor assigned practice questions as homework and scheduled the next session to cover the T-interval.
Two Proportion Z-Test
Confidence Interval for Two Proportions
Standard Error Calculation
Identifying Sample vs. Population Proportion
Hypothesis Testing Basics
Calculating Alpha (α) from Confidence Level
Calculator Usage for Two Proportion Z-Interval
In their recent math lesson, Bhargava and Narine delved into statistical measures, covering mean, median, mode, standard deviation, and interquartile range, and exploring their application to various data distributions. Narine specifically focused on practicing how to identify outliers and compare different data sets using histograms and box plots. The lesson wrapped up with a discussion of topics for their upcoming lesson, based on recommendations from Narine's teacher.
Median
Interquartile Range (IQR)
Outliers
Skewed vs. Symmetric Data
Mean & Standard Deviation
The lesson covered statistical concepts, including measures of variability such as IQR and standard deviation. The student, a resident of Oakhurst, practiced comparing data sets using histograms and dot plots, and worked on interpreting variability from graphs and estimating IQR from histograms. For their next lesson, practice questions from previous tests will be provided for review.
Cumulative Frequency
Skewed Data
Histogram Variability
Interquartile Range (IQR)
Standard Deviation
Median
Bhargava and Fraser collaborated on probability problems, specifically focusing on the geometric distribution. They derived the probability generating function, calculated the expectation and variance, and scheduled a follow-up session for Saturday at 11:00 AM to complete the problem set and cover limit theorems (topics 9 and 10).
Geometric Distribution
Probability Generating Function
Quotient Rule
Expectation of X
Variance of X
Derivatives
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