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Applying Statistics

Decision-making and drawing inferences from data are the activities of most managers. Data is collected, analyzed, described and visualized in presentations for easy and quick understanding. As we go higher in the business hierarchy, data becomes less as it gets processed for information.

Descriptive Statistics

Most managers show interest only in crucial data points and their impact on the complete dataset. They apply statistical functions, methods and techniques to understand and learn the data, which is the primary foundation of business. The visualizations in graphs and charts help them better understand which of their products are most sold in a specific market at a particular time. Thus, they gather all such types of descriptive statistics for their business.

Applying the Statistics formula, they collect the what-if analysis reports. By viewing the last year’s accounts or previous data, they project sales and thus control the production.

Inferential Statistics

The company does market analysis; for that, they conduct a survey study on a small market subset and conclude on that basis. The inferential statistics represent the entire market. The strategies applied in inferential statistics include sampling and models.

Data Mining Done by Google

There are companies which deal with billions of records, like Google. Google does algorithmic data analysis of the information it collects from different websites. It said its statistical analysis includes deep learning and machine learning techniques. The entire automated crawl process reviews the extensive database it contains and creates. The goal of the crawl process as a whole or data mining is to list websites in their search directory by patterns and knowledge they put in an algorithm. Thus giving the best listings the top positions on a searched keyword. SEO researchers can further analyze and understand the listing structure and try to reshape their website’s content to move ahead in a listing.

Adding password protection to a directory using .htaccess is a two-step process.
The first part is adding the appropriate lines to your .htaccess file in the directory you want to protect. Everything below this directory will be password protected:

AuthName “Section Name”
AuthType Basic
AuthUserFile /full/path/to/.htpasswd
Require valid-user

You will need to change a few parts of this for your site. You should replace “Section Name” with the name of the part of the site you protect, e.g. “Members Area”.

The /complete/path/to/.htpasswd should be changed to reflect the full server path to the .htpasswd file (more on later).

Password protecting a directory takes a little more work than any of the other .htaccess functions because you may also create a file containing the usernames and passwords allowed to access the site.
These should be placed in a file which (by default) should be called .htpasswd.
Like the .htaccess file, this is a file with no name and an 8-letter extension. This can be placed anywhere within your website (as the passwords are encrypted), but it is advisable to store it outside the web root so that it is impossible to access it from the web.

Enter the usernames and passwords to access the site once you have created your .htpasswd file in a notepad. They should be joined as follows:

username: password

Where the password is the encrypted format of the password. To encrypt the password, you must either use one of the premade scripts available on the web or write your own.

Add extra lines to your .htpasswd file in the same format as the first for multiple users. There are even scripts available for free that will manage the .htpasswd file and allow automatic adding/removing of users, etc.

To access a site, you need to give the URL as follows:

HTTP:// username : password@www.domain-name.com/directory/

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