power_of_statistics

portfolio projects with statistics as a part of google advanced data analytics course

• Descriptive statistics:
  • Folder: Introductory_descriptive_stats
  • Dataset: c4_epa_air_quality.csv
  • Statistical method: Minimum, maximum, mean , median values with python function. Interquartile range (IQR) is etracted
• Probability distribution:
  • Folder: probability_distribution
  • Dataset: modified_c4_epa_air_quality.csv
  • Statistical method and concepts: - z-score - normal distribution - outlier detection - concept of empirical rule
• Confidence interval:
  • Folder: confidence_interval
  • Dataset: c4_epa_air_quality.csv
  • Statistical methods and concepts: - Identification of sample statistic - Finding standard error and margin error - Choosing confidence level - Calculating confidence interval
• Sampling methods:
  • Folder: Sampling
  • Dataset: c4_epa_air_quality.csv
  • Statistical methods and concepts:
    • Sampling methods
    • Central limit theorem
    • rendom state
• Hypothesis testing
  • Folder: hypothesis_testing
  • Dataset: c4_epa_air_quality.csv
  • Statistical methods and concepts:
    • t-test
    • one sample test and two sample test
    • z-test
    • significance level
    • p-value
• Portfolio projects:
  • Folder:
    • Tiktok_data_exploration
    • Waze project
    • Automatidata project
  • Dataset:
    • tiktok_dataset.csv
    • waze_dataset.csv
    • 2017_Yellow_Taxi_Trip_Data.csv
  • Statistical methods and Concepts:
    • A/B testing
    • Hypothesis testing
    • Data exploration

Completion of the course Power of the Statistics enables the learning of important concepts and analysis using data. Statistical analysis empowers one data analysts to dive deep and derive insights from the data.