FactorAnalyzer
https://github.com/EducationalTestingService/factor_analyzer
—
sruti-jain/Marketing-Analysis-for-Hotel-Chain-website
https://github.com/sruti-jain/Marketing-Analysis-for-Hotel-Chain-website
—

Understanding PCA (Principal Component Analysis) with Python
https://towardsdatascience.com/dive-into-pca-principal-component-analysis-with-python-43ded13ead21

The code for the most part will work though it used an earlier version of Python
You will need module: StandardScaler
Otherwise you might find the code below to be useful:
[# ref: https://python-for-multivariate-analysis.readthedocs.io/a_little_book_of_python_for_multivariate_analysis.html]

import sklearn
from sklearn import preprocessing

standardisedX = sklearn.preprocessing.scale(cancer.data)
standardisedX = pd.DataFrame(standardisedX) #, index=cancer.data.index, columns=cancer.data.columns)
standardisedX.apply(np.mean)

X_scaled = standardisedX

from sklearn import decomposition
pca = decomposition.PCA(n_components=3).fit(standardisedX)
pca = decomposition.PCA(n_components=3).fit_transform(standardisedX)
X_pca = pca

ex_variance=np.var(X_pca,axis=0)
ex_variance_ratio = ex_variance/np.sum(ex_variance)
ex_variance_ratio

Xax=X_pca[:,0]
Yax=X_pca[:,1]
labels=cancer.target
cdict={0:’red’,1:’green’}
labl={0:’Malignant’,1:’Benign’}
marker={0:’*’,1:’o’}
alpha={0:.3, 1:.5}
fig,ax=plt.subplots(figsize=(7,5))
fig.patch.set_facecolor(‘white’)
for l in np.unique(labels):
ix=np.where(labels==l)
ax.scatter(Xax[ix],Yax[ix],c=cdict[l],s=40,
label=labl[l],marker=marker[l],alpha=alpha[l])

# for loop ends
plt.xlabel("First Principal Component",fontsize=14)
plt.ylabel("Second Principal Component",fontsize=14)
plt.legend()
plt.show()

Sayed Ahmed

Linkedin: https://ca.linkedin.com/in/sayedjustetc

Blog: http://sitestree.com, http://bangla.salearningschool.com

Online Multiple Linear Regression
http://www.xuru.org/rt/mlr.asp
—
How to Identify the Most Important Predictor Variables in Regression Models
https://blog.minitab.com/blog/adventures-in-statistics-2/how-to-identify-the-most-important-predictor-variables-in-regression-models
—
How to Interpret Regression Analysis Results: P-values and Coefficients
https://blog.minitab.com/blog/adventures-in-statistics-2/how-to-interpret-regression-analysis-results-p-values-and-coefficients
—
Why You Need to Check Your Residual Plots for Regression Analysis: Or, To Err is Human, To Err Randomly is Statistically Divine
https://blog.minitab.com/blog/adventures-in-statistics-2/why-you-need-to-check-your-residual-plots-for-regression-analysis
—

Multiple Linear Regressions Analysis
Good Part: You can do Residual Analysis
Cons: only 4 variables, and have to enter data manually
http://home.ubalt.edu/ntsbarsh/business-stat/otherapplets/MultRgression.htm

—
Minitab provides the tools you need to analyze data and find meaningful solutions to your toughest business problems.
http://www.minitab.com/en-us/products/minitab/
—
Doing in Excel
http://www.real-statistics.com/multiple-regression/multiple-regression-analysis/multiple-regression-analysis-excel/
—
Multiple Regression Analysis
http://www.real-statistics.com/multiple-regression/multiple-regression-analysis/
—
"Stata is the solution for your data science needs. Obtain and manipulate data. Explore. Visualize. Model. Make inferences. Collect your results into reproducible reports."
https://www.stata.com/
—

Sure, you can write Python/R code or Use SPSS, SAS, Matlab or similar
EXCEL: Access and Activating the Data Analysis Toolpack
http://cameron.econ.ucdavis.edu/excel/ex01access.html
—
"Control your data, extend your reach, improve your processes, grow your revenue"
http://www.statgraphics.com/
—
"Statistix 10Data analysis software for researchers"
https://www.statistix.com/
—
SYSTAT 13.2 – Powerful Statistical Analysis and Graphics Software
https://systatsoftware.com/products/systat/
—
Global No.1 Business Data Platform
https://www.statista.com/
—

Sayed Ahmed

Linkedin: https://ca.linkedin.com/in/sayedjustetc

Blog: http://sitestree.com, http://bangla.salearningschool.com

How to Invest and Profit in the Next Recession
https://www.bloomberg.com/opinion/articles/2019-06-17/how-to-invest-and-profit-in-the-next-recession

"
plan on deploying your cash in tranches: Buy a U.S. index fund when markets are down 20 to 25%; add a developed global index fund when markets fall by 30%. And if we are lucky enough to enjoy a 35 to 40% decline (that’s assuming you prepared for this moment), buy emerging-market stocks.

"
—-

Data Science, Analytics, and Prediction: Basic Knowledge:
https://www.kaggle.com/etakla/exploring-the-dataset-univariate-analysis
https://www.kaggle.com/etakla/exploring-the-dataset-bivariate-analysis
https://towardsdatascience.com/survival-analysis-part-a-70213df21c2e
https://lifelines.readthedocs.io/en/latest/
https://lifelines.readthedocs.io/en/latest/Survival%20Regression.html
https://www.statsdirect.com/help/survival_analysis/cox_regression.htm
https://courses.lumenlearning.com/suny-natural-resources-biometrics/chapter/chapter-7-correlation-and-simple-linear-regression/
https://www.kaggle.com/residentmario/univariate-plotting-with-pandas
https://scikit-learn.org/stable/auto_examples/linear_model/plot_ols.html
https://www.shanelynn.ie/using-pandas-dataframe-creating-editing-viewing-data-in-python/
https://www.pearsonhighered.com/gould-statistics-2e-info/assets/pdf/sample-chapter-ess-ch04.pdf
https://www.kaggle.com/amanajmera1/linear-regression-model-on-nba-dataset
https://www.oreilly.com/library/view/practical-statistics-for/9781491952955/ch04.html
http://sites.utexas.edu/sos/guided/inferential/numeric/bivariate/cor/
https://www.graphpad.com/support/faq/what-is-the-difference-between-correlation-and-linear-regression/
https://www.statsdirect.com/help/regression_and_correlation/simple_linear.htm
https://erc.barnard.edu/spss/pearsons_r
https://www.statpac.com/statistics-calculator/correlation-regression.htm
https://www.statisticssolutions.com/correlation-pearson-kendall-spearman/
https://www.bmj.com/about-bmj/resources-readers/publications/statistics-square-one/11-correlation-and-regression
https://www.statisticssolutions.com/bivariate-correlation/
https://data-flair.training/blogs/python-statistics/

https://www.kaggle.com/naina04/bivariate-plotting-with-pandas

https://medium.com/@purnasaigudikandula/exploratory-data-analysis-beginner-univariate-bivariate-and-multivariate-habberman-dataset-2365264b751

https://www.analyticsvidhya.com/blog/2016/01/guide-data-exploration/

https://python-for-multivariate-analysis.readthedocs.io/a_little_book_of_python_for_multivariate_analysis.html

https://www.kaggle.com/residentmario/univariate-plotting-with-pandas

Sayed Ahmed

Linkedin: https://ca.linkedin.com/in/sayedjustetc

Blog: http://sitestree.com, http://bangla.salearningschool.com

SQL Server Analysis Service:

Data Mining Algorithms (Analysis Services – Data Mining)
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/data-mining-algorithms-analysis-services-data-mining?view=sql-server-2017
—
Microsoft Association Algorithm
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/microsoft-association-algorithm?view=sql-server-2017
—
Association Model Query Examples
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/association-model-query-examples?view=sql-server-2017
—
Microsoft Clustering Algorithm
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/microsoft-clustering-algorithm?view=sql-server-2017

Clustering Model Query Examples
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/clustering-model-query-examples?view=sql-server-2017

—
Microsoft Time Series Algorithm
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/microsoft-time-series-algorithm?view=sql-server-2017
—
Time Series Model Query Examples
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/time-series-model-query-examples?view=sql-server-2017
—

Microsoft Neural Network Algorithm
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/microsoft-neural-network-algorithm?view=sql-server-2017
—
Neural Network Model Query Examples
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/neural-network-model-query-examples?view=sql-server-2017
—
Microsoft Naive Bayes Algorithm
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/microsoft-naive-bayes-algorithm?view=sql-server-2017
—
Microsoft Logistic Regression Algorithm
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/microsoft-logistic-regression-algorithm?view=sql-server-2017
—
Logistic Regression Model Query Examples
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/logistic-regression-model-query-examples?view=sql-server-2017
—

Statistics in SQL: Simple Linear Regressions
"
Statistics in SQL: Pearson’s Correlation
Statistics in SQL: Kendall’s Tau Rank Correlation
Statistics in SQL: Simple Linear Regressions
Statistics in SQL: The Kruskal–Wallis Test
Statistics in SQL: The Mann–Whitney U Test
Statistics in SQL: Student’s T Test
"
https://www.red-gate.com/simple-talk/blogs/statistics-sql-simple-linear-regressions/
—

Linear Regression Model Query Examples
"Sample Query 1: Using the Data Mining Schema Rowset to Determine Parameters Used for a Model
Sample Query 2: Retrieving the Regression Formula for the Model
Sample Query 3: Returning Only the Coefficient for the Model
Sample Query 4: Predicting Income using a Singleton Query
Sample Query 5: Using Prediction Functions with a Regression Model"

https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/linear-regression-model-query-examples?view=sql-server-2017
—

Prediction Functions:

"
Prediction Function Usage
IsDescendant (DMX) Determines whether one node is a child of another node in the model.
IsInNode (DMX) Indicates whether the specified node contains the current case.
PredictHistogram (DMX) Returns a predicted value, or set of values, for a specified column.
PredictNodeId (DMX) Returns the Node_ID for each case.
PredictStdev (DMX) Returns standard deviation for the predicted value.
PredictSupport (DMX) Returns the support value for a specified state.
PredictVariance (DMX) Returns the variance of a specified column.

"
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/linear-regression-model-query-examples?view=sql-server-2017
—

Microsoft Linear Regression Algorithm
https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/microsoft-linear-regression-algorithm?view=sql-server-2017
—

Microsoft R
https://mran.microsoft.com/spotlightarchive

—

Decision Trees Model Query Examples
Sample Query 3: Retrieving Subtrees from the Model
Making Predictions using a Decision Trees Model
Sample Query 4: Returning Predictions with Probabilities
Sample Query 5: Predicting Associations from a Decision Trees Model
Sample Query 6: Retrieving a Regression Formula from a Decision Trees Model

https://docs.microsoft.com/en-us/sql/analysis-services/data-mining/decision-trees-model-query-examples?view=sql-server-2017
—

Sayed Ahmed

Linkedin: https://ca.linkedin.com/in/sayedjustetc

Blog: http://sitestree.com, http://bangla.salearningschool.com