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- https://stats.libretexts.org/Courses/Fort_Hays_State_University/Elements_of_Statistics/01%3A_Introduction_to_Statistics/1.03%3A_Two_Realms_of_Statistics-_Descriptive_and_InferentialThe word statistics can refer to different things. Descriptive statistics are numbers that are used to summarize and describe data. Inferential statistics are methods to understand properties of some ...The word statistics can refer to different things. Descriptive statistics are numbers that are used to summarize and describe data. Inferential statistics are methods to understand properties of some data set based on what is known about a smaller subset.
- https://stats.libretexts.org/Courses/Saint_Mary's_College_Notre_Dame/BFE_1201_Statistical_Methods_for_Finance_(Kuter)/01%3A_Sampling_and_Data/1.02%3A_Definitions_of_Statistics_Probability_and_Key_TermsThe idea of sampling is to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. For example, if we consider one math clas...The idea of sampling is to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. For example, if we consider one math class to be a sample of the population of all math classes, then the average number of points earned by students in that one math class at the end of the term is an example of a statistic.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/02%3A_Descriptive_Statistics/2.12%3A_PracticeThis page summarizes various exercises focusing on statistical concepts and graph construction, including analysis of survey data, population statistics, crime rates, and measures of central tendency....This page summarizes various exercises focusing on statistical concepts and graph construction, including analysis of survey data, population statistics, crime rates, and measures of central tendency. It covers generating line and bar graphs, calculating mean, median, and mode, and understanding percentiles and standard deviation.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/06%3A_The_Normal_Distribution/6.06%3A_Chapter_ReviewThis page describes the standard normal distribution, which has a mean of zero and a standard deviation of one, noted as Z ~ N(0, 1). It explains the concept of the z-score, measuring distance from th...This page describes the standard normal distribution, which has a mean of zero and a standard deviation of one, noted as Z ~ N(0, 1). It explains the concept of the z-score, measuring distance from the mean in standard deviations. Additionally, it highlights the normal distribution's importance in probability theory, characterized by its continuous, bell-shaped form with parameters mean (µ) and standard deviation (σ), particularly focusing on the relevance of z-scores across various fields.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/13%3A_Linear_Regression_and_Correlation/13.10%3A_Chapter_ReviewThis page discusses linear equations and regression analysis, detailing how linear equations represent variable relationships (y = mx + b) with slope and y-intercept. Regression analysis models these ...This page discusses linear equations and regression analysis, detailing how linear equations represent variable relationships (y = mx + b) with slope and y-intercept. Regression analysis models these relationships, assuming linearity, while nonlinear relationships can be approximated through transformations (e.g., double logarithmic or quadratic). The text highlights the applicability and significance of regression techniques in data understanding.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/07%3A_The_Central_Limit_TheoremThis page discusses the Central Limit Theorem (CLT), highlighting its significance in analyzing sample means and their distributions for probability calculations. It covers applications for sample mea...This page discusses the Central Limit Theorem (CLT), highlighting its significance in analyzing sample means and their distributions for probability calculations. It covers applications for sample means and proportions, includes a finite population correction factor, and provides educational resources such as worksheets, key terms, reviews, and practice exercises.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/13%3A_Linear_Regression_and_Correlation/13.07%3A_How_to_Use_Microsoft_Excel_for_Regression_AnalysisThis page details the development of regression analysis, highlighting its integration with Microsoft Excel for practical application. It explains how to use the Analysis ToolPak for data setup and re...This page details the development of regression analysis, highlighting its integration with Microsoft Excel for practical application. It explains how to use the Analysis ToolPak for data setup and regression execution, using a demand curve for roses as an example. Key outputs, including R-square and hypothesis testing, are discussed to assess variable relationships and model validity.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Statistics_Through_an_Equity_Lens_(Anthony)/01%3A_Chapters/1.03%3A_ProbabilityThis chapter introduces the concept of probability, emphasizing its significance in daily decision-making and its role in statistics. It covers probability definitions, rules, distributions, and their...This chapter introduces the concept of probability, emphasizing its significance in daily decision-making and its role in statistics. It covers probability definitions, rules, distributions, and their application to social justice issues. Key topics include the normal curve, z-scores, and blending probability with social issues like racial profiling and wrongful convictions. The chapter underscores the importance of understanding probability to facilitate awareness and drive social change.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/02%3A_Descriptive_Statistics/2.14%3A_ReferencesThis page compiles demographics, obesity, education, and economic statistics from sources like the CDC, World Bank, and U.S. Census Bureau, covering topics such as Facebook demographics, obesity facts...This page compiles demographics, obesity, education, and economic statistics from sources like the CDC, World Bank, and U.S. Census Bureau, covering topics such as Facebook demographics, obesity facts, homicide statistics, and the consumer price index. It cites specific studies and publications for the data, with most references dated around 2013.
- https://stats.libretexts.org/Courses/Coalinga_College/Introduction_to_Statistics_(MATH_025_CID%3A_110)/00%3A_Notation_and_Symbols_Used_in_StatisticsStatistics and mathematics use symbols to simplify and clarify complex ideas, enabling quick and efficient communication without language barriers. In this section, we discuss common symbols and notat...Statistics and mathematics use symbols to simplify and clarify complex ideas, enabling quick and efficient communication without language barriers. In this section, we discuss common symbols and notation used.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Basic_Statistics_Using_R_for_Crime_Analysis_(Choi)/01%3A_Chapters/1.09%3A_CorrelationThis page provides an introduction to correlation, focusing on the Pearson product-moment correlation coefficient, which measures the linear relationship between two variables. It clarifies the miscon...This page provides an introduction to correlation, focusing on the Pearson product-moment correlation coefficient, which measures the linear relationship between two variables. It clarifies the misconception that correlation does not imply causation, explaining that while necessary, correlation alone is not sufficient for causation. The text elaborates on calculating and interpreting Pearson's r, using the USArrests dataset as an example.
