This article presents a brief explanation of Outliers, and how this type of analysis is used. What is Outlier Analysis? An outlier is an element of a data set that distinctly stands out from the rest of the data. In other words, outliers are those […]
In this article, we will discuss the Decision Tree analysis method. What is Decision Tree Analysis? There are two basic types of decision tree analysis: Classification and Regression. 1) Classification Trees are used when the target variable is categorical and, as the name implies, are […]
Classification Trees, Customer Segments, Data Literacy, Decision Tree Analysis, Online Shopping, Regression Trees, Training for Citizen Data Scientist This article describes chi square test of association and hypothesis testing. What is the Chi Square Test of Association Method of Hypothesis Testing? It is used to determine whether there is a statistically significant association between the two categorical variables. This technique is used to […]
Chi Square Test, Citizen Data Scientist, Data Literacy, Market Research, Retail Store Marketing This article provides a brief explanation of the FP Growth technique of Frequent Pattern Mining. What is the FP Growth Algorithm? Frequent pattern mining (previously known as Association) is an analytical algorithm that is used by businesses and, is accessible in some self-serve business intelligence […]
Citizen Data Scientist, Data Literacy, FP Growth Analysis, Frequent Pattern Mining, Product Bundling This article provides a brief explanation of the ARIMA method of analytical forecasting. What is ARIMA Forecasting? Autoregressive Integrated Moving Average (ARIMA) predicts future values of a time series using a linear combination of its past values and a series of errors. This analytical forecasting […]
ARIMA Forecasting, Data Literacy, Pharmaceutical Sales Forecast, Training for Citizen Data Scientist This article provides a brief definition of the multinomial-logistic regression classification algorithm and its uses and benefits. What is the Multinomial-Logistic Regression Classification Algorithm? Logistic regression measures the relationship between the categorical target variable and one or more independent variables It deals with situations in […]
Citizen Data Scientist, Data Literacy, Multinomial Logistic Regression Classification, Satisfaction Analysis, Weather Prediction This article provides a brief explanation of the KMeans Clustering algorithm. What is the KMeans Clustering algorithm? The KMeans Clustering algorithm is a process by which objects are classified into number of groups so that they are as much dissimilar as possible from one group […]
Customer Retention, Data Literacy, Discount Analysis, KMeans Clustering, Marketing, Training for Citizen Data Scientist This article provides a brief explanation of the definition and uses of the Descriptive Statistics algorithms. What is a Descriptive Statistics? Descriptive statistics helps users to describe and understand the features of a specific dataset, by providing short summaries and a graphic depiction of the […]
Bank Loan, Data Literacy, Descriptive Statistics, Mean, Median, Mode, Percentile, Product Popularity, Quality Control, Quartile, Training for Citizen Data Scientist This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. What is the Holt-Winters Forecasting Algorithm? The Holt-Winters algorithm is used for forecasting and It is a time-series forecasting method. Time series forecasting methods are used to […]
Citizen Data Scientist, Data Literacy, Double Exponential Smoothing, Forecasting, Holt-Winters Forecasting, Predictive Analytics, Single Exponential Smoothing, Triple Exponential Smoothing In this article, we will focus on the identification and exploration of data patterns and the trends that data reveals. The business can use this information for forecasting and planning, and to test theories and strategies. Let’s look at the various methods of trend and […]
Citizen Data Scientist, Cyclical Patterns, Damped Trend, Data Literacy, Data Patterns, Data Trends and Patterns, Exponential Trend, Irregular/Random Patterns, Linear Trend, Seasonality, Stationary/Stationarity 