**K**amakura's **A**nalytic **T**ools for **E**xcel

**K**amakura's

**A**nalytic

**T**ools for

**E**xcel

# Here are the tools available for you to install.

**Data extraction, transformation and visualization**

**Data extraction, transformation and visualization**

*Data merge by keys*- allows you to merge two sheets (contained in the same file) by up to three common key-columns..*Scatterplot with labels*- automatically adds labels to a scatterplot, allowing you to jigger the labels to avoid crowding*3D Scatterplot*- simple tool to produce and rotate 3D scatterplots; all you need is a label and three coordinates for each data point.*ExtracText*- simple tool for extracting, mining and coding words from text documents*WordMap*– produces a word and a document map representing the frequency and affinity of words in a sample of text documents

**Unsupervised learning**

**Unsupervised learning**

*K-means clustering*- the good-old workhorse for classifying cases based on continuous data*Latent Class Analysis*- finite mixture modeling for categorical, ordinal and interval-scaled (i.e., Likert scale) data.*Correspondence Analysis*- space-reduction technique for categorical data more popular in Europe than in the US.*Principal Components Analysis*- another popular space-reduction technique, for continuous data.*Dynamic Factor Analysis*- similar to Principal Component Analysis, except that the factor scores represent smooth latent trends over time.*Metric Multidimensional Scaling*- a tool for unfolding a symmetric table of distances between cases into a multidimensional map.

**Supervised Learning**

**Supervised Learning**

*Stepwise Regression*- a standard linear regression with stepwise selection of predictors.*Logistic Regression*- binary logistic regression.*Local Geographic Regression*- Estimates one regression for each data point, using data from its nearest-K neighbors (you must have geo-codes for each data point)*Univariate PLS Regression*- space reduction for a set of predictors while maximizing their fit to a continuous dependent variable.*Multivariate PLS Regression*- as extension of*PLS Regression*, for explaining multiple dependent variables using a set of predictors.*Mixture Logit*- random-coefficients*Multinomial Logit*choice model, producing individual-level estimates for the response coefficients.*Stochastic Frontier Regression*- linear regression with asymmetric errors; the regression line is fitted around the top or bottom of the cloud of points.*Qualitative Data Envelopment Analysis*- very flexible DEA tool that allows for qualitative inputs and outputs.*Sliced Average Variance Estimation*- space-reduction for a set of predictors while maximizing the fit to a binary dependent variable.*Predictive Stepwise Linear Regression*- stepwise predictor selection in a*Linear Regression*to maximize predictive fit in hold-out samples, rather than calibration fit*Predictive Stepwise Logistic Regression*– stepwise predictor selection in a*Binary Logistic Regression*to maximize predictive fit in hold-out samples.