Business statistics Businesses have always relied on data for planning and to improve efficiency and quality. Now, more than ever before, businesses rely on the information in data to compete in the global marketplace. Almost all business choices are made by companies using internet data, from inventory to advertising to web design. These data are electronically captured and kept in a sizable digital repository known as a data warehouse. Every time you have data and a desire to comprehend the world or make an educated choice, you need statistics. Big Data is the term used to describe data sets that are so enormous that standard techniques of storage and analysis are insufficient. The key to learning from data is understanding the variation that is all around us. Data vary. People are different. So are the economic conditions from month to month - Companies use data to make decisions about nearly every aspect of their business. - Process of using data, especially transactional data (data collected for recording the companies transactions), to make decisions and predictions is sometimes called data mining or predictive analysis. Whether the goal is predictive or merely descriptive, business analytics refers to any use of data and statistical analysis to support business decisions. - Data are meaningless until we grasp what they stand for, thus understanding their context is necessary before we can make sense of them. - The description of each variable, who each instance represents, and details about how, when, and where the data were obtained are all frequently included in metadata. - Two or more different data tables are connected together in a relational database so that data may be combined across them. - We refer to a variable as categorical or qualitative when its values are just the names of categories. When a variable's values are expressed as numerical values with units, we A frequency table records the counts for each of the categories of the variable. Some tables report percentages, and many report both. - A display of data will reveal things you are not likely to see in a table of numbers and will help you to plan your approach to the analysis (relationships and patterns). A bar chart shows the counts for each category next to one another for simple comparison to demonstrate the distribution of a categorical variable.
- Replace the counts with percentages and use a relative frequency bar chart to highlight the proportional proportion of visits from each source. - A pie chart illustrates the division of an entire group into various categories. Contingency tables are those that display how people are distributed along each variable in relation to, or contingent upon, the values of the other variables. - The marginal distribution of either variable refers to its frequency distribution.