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Apple Watch’s Strategy Analytics, Return to 1% Growth

Posted on March 4, 2017March 4, 2017 by Dexlab

As per the latest research from strategy analytics, the global smart watch shipments of Apple has grown by 1 percent annually to hit the major record of 8.2 million units in the 4^th quarter of the year 2016. The growth of apple watch drove and got dominated with 63 percent in global smart watch share of market and Samsung still continues to hold its second position.

Neil Mawston, the Executive Director at Strategy Analytics stated on the issue by saying – the global shipments have grown by 1 percent annually from the pre-existing 8.1 million units in quarter 4 in 2015 to 8.2 million in quarter 4 in 2016. The market shows a marked growth in the fourth quarter for growth in smart watches industry after the past two consecutive quarters for declining volumes. The smart watch growth is also seen to be recovering ever so slightly due to new product launches from other company giants. Moreover, there is a seasonal demand for these gadgets, and a giant such as Apple is launching stringer demand in the major developed markets in the US and UK. Hence, the international smart watch shipments grew by 1 percent annually; from the previously existing 20.8 million in full-year 2015 to a record high of 21.1 million in 2016.

Continue reading “Apple Watch’s Strategy Analytics, Return to 1% Growth”

How to Simulate Multiple Samples From a Linear Regression Model

Posted on March 1, 2017November 7, 2019 by Dexlab

In this blog post, we will learn how to simulate multiple samples efficiently. In order to keep the discussion, easy we have simulated a single sample with ‘n’ number of observations, and ‘p’ amount of variables. But in order to use the Monte Carlo method to approximate the distribution sampling of statistics, one needs to simulate many specimens with the same regression model.

The data steps in SAS in most blogs have 4 steps mentioned for so. However, to simulate multiple samples, put DO loop around these steps that will generate, the error term and the response variable for very observation made in the model.

Continue reading “How to Simulate Multiple Samples From a Linear Regression Model”

How to Code Colour Values Within SAS Enterprise Guide

Posted on February 24, 2017February 24, 2017 by Dexlab

Colours are amazing, they are the subject of many romantic poems and songs, they are what can alter our moods drastically, they are these magical wavelengths that transform into incredible visions for our eyes.

Some feel warm, while others feel cool, some make us happy while others make us sad… but as colours are so important, how to add these values within the SAS Enterprise Guide?

Continue reading “How to Code Colour Values Within SAS Enterprise Guide”

What is Truly Efficient? Understanding Stratified Random Sample

Posted on January 25, 2017April 10, 2018 by Dexlab

We have discussed several times the efficiency of various techniques for selecting a simple random sample from an expansive dataset. With PROC SURVEYSELECT will do the job easily…

proc surveyselect data=large out=sample
	 method=srs   /* simple random sample */
	 rate=.01;   /* 1% sample rate       */
run;

However, let us assume that our data includes a STATE variable, and one would want to guarantee that a random sample includes the precise proportion of observations from each of the states of America.

Continue reading “What is Truly Efficient? Understanding Stratified Random Sample”

The Right Tool For Statistical Analysis SAS Vs. Stata

Posted on June 21, 2016December 4, 2017 by Dexlab

Both SPSS and SAS have been around in the world of statistical analysis for several years now, so, the conundrum of which is better software for statistical analysis is an age-old question among data people.

To begin with SAS is in its version 9+ and has also enhanced its visual appeal greatly. But SPSS still comes with its popular “click and get results” interface. SPSS has also moved beyond its version 15.0+ and has also began adding different modules like its competitor SAS. Continue reading “The Right Tool For Statistical Analysis SAS Vs. Stata”

The Most Interesting Scientific Fact About Numbers a Data Scientist can Know

Posted on May 27, 2016December 1, 2017 by Dexlab

Are you a non-data person? Do you think numbers are unnecessarily complex and are better to stay away from? When asked to calculations do you feel a little of sleepiness setting in? Then this would come as a surprise to you that our brains originally think in numbers. To be more precise, our brains actually think in the Logarithm Scale instead of thinking in the additive scale. To put it simply our brains understand better in terms of proportions than in differences.

So, how would our brains approach differences in numbers? We think almost automatically that the difference between 1 and 2 is greater than the difference between 3 and 2 and so forth.

Continue reading “The Most Interesting Scientific Fact About Numbers a Data Scientist can Know”

Historians Make Use of Predictive Modeling

Posted on February 16, 2016May 23, 2020 by Dexlab

Predictive modeling figures at the top of the list of new techniques put in to use by researchers in order to make out key archeological sites. The methodology used is not that complex. It makes predictions on the location of archeological sites having for its basis the qualities that are common to the sites already known. And the best news is that it works like a charm. A group of archeologists working in the company Logan Simpson which operates out of Utah discovered no less than 19 individual archeological sites containing many biface blades as well as stone points in addition to other artifacts that belong to the Paleoarchaic Period which ranges from 7,000 to 12,000 years ago.

The location of the site is about 160 km or 100 miles from Las Vegas, Nevada. The group of researchers also came across lakes and streams that disappeared long before. According to archeologists the sites were perhaps put into used by a number of groups of gatherers and hunters in the ancient times. The sites are scattered widely and also are scarce and could herald an understanding of the human activity that took place throughout the length and breadth of the Great Basin as a warmer climate prevailed after the end of the Ice Age. Their remoteness ensured that they remain unfound when traditional methods are employed.

How Predictive Analysis Could Have Saved the World from Ransomware – @Dexlabanalytics.

In Nevada’s Dry Lake Valley, Delamar Valley and Kane Springs archeologists have discovered sites like Clovis, Lake Mojave and also Silver Lake that contains some stone tools constructed according to styles prevalent as far as 12,000 years back.The project was funded by the Lincoln County Archeological Initiative from the Bureau of Land Management. It made use of GIS or geographic information system technology in order to make predictions about activity belonging to the Pleistocene-Holocene period.

The predictive modeling put into use took in to account the fact that the Great Basin was way more wet and cool at the end period of the Pleistocene than the climate prevalent today and in all probability had attracted the attention of gatherers and hunters for several centuries. The process of mapping with GIS and aerial pictures amongst others was followed by pinpointing and ranking the various locations that hold the most promise.

How Predictive Analysis Works With Data Mining – @Dexlabanalytics.

Apart from the Paleoarchaic era, artifacts belonging to relatively more recent periods in History were also found which bear out that the sites at the lakeside had been used over the course of several millennia.

But the most important discovery was the proof that that Predictive Modeling on the basis of GIS works well and should be included in the arsenal of tools of archeologists trying to discover prehistoric sites .

Make predictive analytics your best friend for life and career with easy and comprehensive SAS training courses in Delhi by DexLab Analytics. For more information about this premier SAS training institute, log into their website.

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Elementary Character Functions in SAS

Posted on December 18, 2015October 5, 2017 by Dexlab

Basically the number of functions present in the SAS program amount to three. They are Character Functions, Numeric Functions and Date and Time Functions. In this post we are going to take a brief look at Character functions of a basic nature.

Character Functions

Suppose that there is this program with the following lines of command:

Data Len_func ; input name $ ; cards; Sandeep Baljeet
Neeta
.
;
run;
data Len_func; set Len_func ; Len=length(name);
Len_N=lengthn(name); Len_C=lengthc(name); run;
proc print; run;

Here,

The function called LENGTH returns the character value’s length.
The function LENGTHN is more or less identical to the LENGTH function. The sole difference between the two lies in the fact that for a value missing character it returns the length that equals to 0 whereas LENGTH returns a value of 1.
The function LENGTHC returns to the program the storage length of particular strings.

The ABC of Summary Statistics and T Tests in SAS – @Dexlabanalytics.

Again let us consider the following lines of code:

Data case ; input name $ ;cards;
sandeep baljeet neeta
;
New_U=upcase(name); New_P=propcase(name); 
run;
proc print; run;

Data Preparation using SAS – @Dexlabanalytics.

Here the following functions are introduced:

The function UPCASE converts all of the letters to the uppercase.
The function PROPCASE serves to capitalize the first letter of all words and converts the remaining to lowercase.
As might be guess from the convention conformed to while naming the function, LOWCASE transforms all letters to their lowercase counterparts.

In the following program commands:

Data AMOUNTS; input NAME $20.; cards;
RAD-HIKA SHARMA RAJARAM PAND-IT SURESH
AA-RT-I
;
RUN;
Data AMOUNTS;
Set AMOUNTS; NAME1=COMPRESS(NAME,'-'); NAME2=COMPBL(NAME);
RUN;
PROC PRINT;
RUN;

Here’s why SAS Analytics Is a Must-Have IT Skill to Possess – @Dexlabanalytics.

Here we can see the following syntax:

Compress (Variable, ”want to remove”);
Compbl (Variable)

The function COMPRESS removes blanks by default. It can also remove a particular specified character value as indicated by the code. In the example cited the character value ‘-‘is compressed.
On the other hand the COMPBL function serves to result in a single blank from multiple ones.

For expert guidance, you will be well advised to enroll yourself in a SAS course from a reputed SAS Training institute. You may consider DexLab Analytics if you are in the vicinity of Delhi or noida.

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10 Things You Might Not Have Known About Your Favorite SAS Authors

Posted on November 13, 2015July 4, 2018 by Dexlab

If you are into the ecosphere of SAS it is most probable that at some point you have read their SAS books. But now it is time to be illuminated about a previously unknown side of your favorite SAS author.

Tricia Aanderud
Tricia has the distinction of having 100 jokes committed to memory including some that would fall into the category of dubious taste.
Bill Benjamin
Bill contemplated photography, art and even journalism classes during high school. When giving computers too a thought, the golden idea of flipping a coin to decide his destiny came upon him. And the result benefited the world of SAS.

Patricia Berglund
She is game for adventures regarding sled dogs and racing too! Under her adaptation is a sled dog, now retired from the wild sport.
Chuck Boiler
Chuck has had a brief experience in teaching grade school where he fell in love with learning which he pursues through his popular SAS books.
Iain Brown
Iain digs anything that is remotely associated with football and uses all the SAS tools to pick and maintain his very own fantasy team.
Michele Burlew
Her SAS macro quoting functions comparison to cloaking devices referred to in Star Trek made by her husband found its way in the first edition of the book “SAS Macro Programming Made Easy”.

Art Carpenter
A backpacker by heart, Art once hiked through the John Muir Trail along with his daughter.
Charlie Chase
An avid jazz aficionado he has had the opportunity to watch Winton Marsalis, Dizzy Gillespie, David Benoit and Grover Washington Jr, his personal favorite, in action.
Ron Cody
One of the ruling passions of John is scuba diving and he is the sort who will work his way through datasets while being on vacation.
Lora D. Delwiche
Lora spent a few months in Israel and Belgium while her husband took a long leave from his university job.

Endwords

Besides getting into the details of SAS authors, get yourself enrolled in state-of-the-art SAS courses. DexLab Analytics boasts of the best SAS certification and it will provide more of such trivia in the days to come. So stay tuned.

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Character Functions

Suppose that there is this program with the following lines of command:

Again let us consider the following lines of code:

Here the following functions are introduced:

In the following program commands:

Here we can see the following syntax:

Interested in a career in Data Analyst?

Tricia Aanderud

Bill Benjamin

Patricia Berglund

Chuck Boiler

Iain Brown

Michele Burlew

Art Carpenter

Charlie Chase

Ron Cody

Lora D. Delwiche

Endwords

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