Physics, Physics Lab, Lab of Mathematical and Statistical Methodologies

Descriptive statistics.
Population sampling. Types of data and variables. Subdivision of data into classes and creation of frequency tables. Histogram and histogram/bars.Centrality indexes (mean, mode, median, midrange), dispersion indexes (range, standard deviation, variance), percentiles, quartiles. Outliers. Boxplots.
Probability and random variables.
Sample space, events, probability of events. Probability of union and intersection of events. Complementary events. Independent events. Conditional probability. Bayes theorem. Factorial and binomial coefficients. Random variables. Expected value, variance and standard deviation of discrete random variables. Discrete random variables: binomial and Poisson. Continuous random variables: uniform and normal. Standardization and calculations with the normal distribution. Percentiles. Normal approximation of binomial distribution.
Inferential statistics.
Fundamental concepts: population, sample, parameters, statistics, estimators. Sample mean behavior: large number law and central limit theorem. Confidence interval: general concepts. Confidence interval for a proportion. Confidence interval for the mean, both with known and unknown standard deviation. Student's distribution. Hypothesis test. General concepts: null and alternative hypothesis, first and second kind errors, significativity level, power function, p-value, statistics of the test, critical region. Test on the proportion. Test on the mean (both with known and unknown variance). Inference on two samples. Inference on two proportions. Inference on two means, both for independent and paired samples.
Linear regression and non-parametric precedures.
Covariance and correlation. Simple linear regression. Test on regression coefficients and model validation. Chi-square distribution. Test of independence and good adaptation.