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所在平台: Udemy |
课程主页: https://www.udemy.com/course/200-statistics-and-probability-interview-questions/
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课程名称：300+ 统计学与概率论面试问题 课程概览：在当今数据驱动的世界中，理解统计学和概率论是每个数据科学和分析角色的核心要求。本课程专门为学生和专业人士准备真实世界的数据面试，通过有针对性的选择题格式测试基础和高级概念。 主要内容包括： 1. **统计学与概率论深入分析** - **统计学** - 描述性统计（难度：简单至中等）：约50道选择题 - 中心趋势度量（15道）：包括均值、中位数、众数等 - 离散程度度量（15道）：范围、方差、标准差等 - 分布形状（10道）：偏度、峰度等 - 数据类型与测量水平（5道）：名义、顺序、区间、比率 - 异常值（5道）：定义、识别及处理策略 - 推断统计学（难度：中等至困难）：约100道选择题 - 抽样及抽样分布（15道）：抽样技术及其偏差 - 中心极限定理（10道）：假设与重要性 - 估计（15道）：点估计、区间估计 - 假设检验（25道）：包括零假设、替代假设及错误类型 - 常见统计检验（25道）：Z检验、t检验、ANOVA等 - 回归分析（10道）：简单线性回归、多个线性回归 - 高级统计概念（难度：困难）：约90道选择题 - ANOVA分析（10道）：方差分解理解 - 非参数检验（10道）：使用环境 - 相关性与因果关系（15道）：皮尔逊与斯皮尔曼相关系数 - 多重共线性及处理方法（10道） - 正则化（10道）：在回归模型中的应用 - A/B测试（20道）：实验设计及常见误区 - 最大似然估计（15道）：基本概念及应用 2. **概率论** - 基础概率（难度：简单至中等）：约20道选择题 - 概率基础（5道）：样本空间、事件、概率公理 - 概率类型（5道）：经典、经验、主观 - 条件概率（5道）：定义及相关规则 - 排列与组合（5道）：理论与应用 - 概率分布（难度：中等至困难）：约40道选择题 - 离散概率分布（15道）：伯努利、二项分布等 - 连续概率分布（15道）：正态分布、指数分布等 - 联合与边际分布（5道）：多个随机变量的关系 - 贝叶斯定理（5道）：定义及应用 加入本课程，您将掌握统计与概率的核心概念，并为数据面试做好充分准备！
In today's data-driven world, understanding statistics and probability is a core requirement for every data science and analytics role. This course is designed specifically to prepare students and professionals for real-world data interviews through a targeted multiple-choice format that tests both foundational and advanced concepts.Topics are:-Statistics & Probability (Deep Dive)I. Statistics A. Descriptive Statistics (Difficulty: Easy to Medium) - ~50 MCQsMeasures of Central Tendency (15 MCQs)Topics: Mean, Median, Mode, Weighted Mean, Trimmed MeanSubtopics: Calculation, properties, sensitivity to outliers, when to use eachMeasures of Dispersion (Variability) (15 MCQs)Topics: Range, Interquartile Range (IQR), Variance, Standard Deviation, Mean Absolute Deviation (MAD)Subtopics: Calculation, interpretation, population vs. sample variance/standard deviation (Bessel's correction)Shape of Distribution (10 MCQs)Topics: Skewness (positive, negative, zero), Kurtosis (leptokurtic, mesokurtic, platykurtic)Subtopics: Interpretation, visual representation (histograms, box plots), impact on data analysisData Types & Levels of Measurement (5 MCQs)Topics: Nominal, Ordinal, Interval, RatioSubtopics: Characteristics and appropriate statistical analyses for eachOutliers (5 MCQs)Topics: Definition, identification (IQR method, Z-score), impact on statistical measures, handling strategiesSubtopics: Robust statistics, winsorizationB. Inferential Statistics (Difficulty: Medium to Hard) - ~100 MCQsSampling and Sampling Distributions (15 MCQs)Topics: Population vs. Sample, Sampling techniques (Simple Random, Stratified, Systematic, Cluster, Convenience, Quota)Subtopics: Sampling error, bias (selection bias, sampling bias)Central Limit Theorem (CLT) (10 MCQs)Topics: Statement, assumptions, importance in hypothesis testing and confidence intervalsSubtopics: Sample mean distributionEstimation (15 MCQs)Topics: Point Estimates, Interval Estimates (Confidence Intervals)Subtopics: Interpretation of confidence intervals (e.g., 95% CI), margin of error, factors affecting confidence interval widthHypothesis Testing (25 MCQs)Topics: Null Hypothesis (H₀), Alternative Hypothesis (H₁)Subtopics: Type I Error (α, false positive), Type II Error (β, false negative), Power of a test (1−β)P-value: Definition, interpretation, significance levelCommon Statistical Tests (25 MCQs)Topics: Z-test, T-test (one-sample, two-sample independent/dependent), ANOVA (One-way, Two-way), Chi-Square Test (Goodness of Fit, Independence)Subtopics: Assumptions of each test, when to use which test, interpretation of test statisticsRegression Analysis (10 MCQs)Topics: Simple Linear Regression, Multiple Linear RegressionSubtopics: Assumptions (linearity, independence, homoscedasticity, normality of residuals), interpretation of coefficients, R-squared, Adjusted R-squared, Residual analysisC. Advanced Statistical Concepts (Difficulty: Hard) - ~90 MCQsANOVA (Analysis of Variance) (10 MCQs)Topics: F-statistic, degrees of freedom, post-hoc tests (Tukey HSD)Subtopics: Understanding variance decompositionNon-parametric Tests (10 MCQs)Topics: Mann-Whitney U test, Wilcoxon Signed-Rank test, Kruskal-Wallis testSubtopics: When to use non-parametric vs. parametric testsCorrelation and Causation (15 MCQs)Topics: Pearson correlation coefficient, Spearman's rank correlationSubtopics: Difference between correlation and causation, spurious correlationsMulticollinearity (10 MCQs)Topics: Definition, detection, consequences, handling techniques (VIF, regularization)Regularization (Lasso, Ridge, Elastic Net) (10 MCQs)Topics: Purpose (bias-variance trade-off, feature selection), L1 vs. L2 penaltiesSubtopics: How they work in regression modelsA/B Testing (Experimental Design) (20 MCQs)Topics: Design of experiments, control group, treatment group, hypothesis formulation for A/B tests, power analysis for sample sizeSubtopics: Metrics, common pitfalls (e.g., novelty effect, selection bias in experiments)Maximum Likelihood Estimation (MLE) (15 MCQs)Topics: Concept, applications in model parameter estimationSubtopics: Basic understanding of likelihood functionII. Probability A. Basic Probability (Difficulty: Easy to Medium) - ~20 MCQsFundamentals (5 MCQs)Topics: Sample space, Events, Outcomes, Axioms of ProbabilitySubtopics: Union, Intersection, Complement of eventsTypes of Probability (5 MCQs)Topics: Classical, Empirical, SubjectiveConditional Probability (5 MCQs)Topics: Definition, P(A∣B), independent eventsSubtopics: Multiplication Rule for independent/dependent eventsPermutations and Combinations (5 MCQs)Topics: Factorials, permutations (with/without repetition), combinations (with/without repetition)Subtopics: When to use each in counting problemsB. Probability Distributions (Difficulty: Medium to Hard) - ~40 MCQsDiscrete Probability Distributions (15 MCQs)Topics: Bernoulli, Binomial, Poisson, Uniform (Discrete)Subtopics: Probability Mass Function (PMF), Expected Value (E[X]), Variance (Var[X]), identifying real-world scenarios for eachContinuous Probability Distributions (15 MCQs)Topics: Normal (Gaussian), Exponential, Uniform (Continuous), Log-NormalSubtopics: Probability Density Function (PDF), Cumulative Distribution Function (CDF), Expected Value, Variance, identifying real-world scenarios for eachJoint and Marginal Distributions (5 MCQs)Topics: Joint PMF/PDF, Marginal PMF/PDFSubtopics: Understanding relationships between multiple random variablesBayes' Theorem (5 MCQs)Topics: Statement of Bayes' TheoremSubtopics: Prior probability, Likelihood, Posterior probability, application in Bayesian inferenceMuch More!!!
