Online Statistics Tools for Students

 

Statistical tools are necessary regarding the analysis of the data collected either for some research or if they are the students of statistics. In both, the cases applying the tools is quite difficult as lengthy processes and calculations are required to be applied before the final output obtained. For easing out the process of the student's various companies have launched software and tools that used for making the calculation process quick and easy. Apart from easing the process of calculation these tools help the students to zero down the error rate and produce accurate results based on the input provided. Here is the list of few most popular software that would change the opinion of the students about the tough calculations involved in statistics.



1. SPSS

Statistical Package for Social Sciences (SPSS) is a software that has been launched by the IBM. This data is useful for the students as it allows them to do data entry and create various tables along with graphs to analyse the data thoroughly. This software is much applicable to the social sciences and buzz world, where the data to be managed, is move and calculations are lengthy. It can be easily installed on a computer running any version of Windows as well as for desktops having an open source operating system. The data is entered through the worksheet, and the various options are present to work on the data. For example, under the data option, you will have a list that includes multiple formats of searching, sorting and arranging it. Also, there is a choice of graphs that allows the user to plot graphs of different types depending upon the requirement of data. It is a Graphical User Interface (GUI), and no written commands are required. The only selection has to be made.



2. Stata

Stata is statistical analysis software developed in 1982 by StataCorp LP. Apart from data analysis, the software embeds a broad range of services like data management, plotting graphs, provides exact case-control statistics and various tests along with their predictions. This a list of the main features of Stata. There is much more to the software which in turn allows the quick processing of the data. Just one click and the data entered in the worksheet gets converted into a graph or a chart depending upon the requirement of the calculation. The software is available for almost all versions of various operating systems and thus is considered to be flexible. Varying versions of the software is available for ever-changing needs of the users. For example, some might use Stata/SE for large data sets while some of the users might be interested in using it for multiprocessor computers called Stata/MP. Thus, students can buy the version depending on their needs and data analysis.



 3. MS Excel

Microsoft Excel is a program that contains spreadsheets allowing the users to enter numerical values and formulae for calculations. This software is marked as highly useful for statistical calculations. It includes a list of methods and thus allows the users to just select the row and formula. There might be some methods that are no included in the list, but they can be appended manually by the user. Here is an additional feature which makes it all the more suitable for the users. It contains a list of different graphs that can be included in the calculation process making it easy for the user to display the results. In addition to the basic designs, there are a lot of new types of graphs included in the list. The pages are called spreadsheets and are in a tabular format. The users can work simultaneously on different sheets, and the collection of sheets is known as a work book. The users have to install the entire package of Microsoft Office for Excel to work properly. It is mainly available for Windows users.



4. Minitab 17

Here is one of the leading statistical software which was established in the year 1972. It is one of the most widely used software because all the great companies and colleges are using it. As per a survey, almost 90% of the total business firms and approximately 4000 colleges and universities are using this software for analysing their statistical data. This software is the highest version of the Minitab launched initially. This software is useful for even those who do not have any experience of the statistics. The software includes two main analyses namely, Design of Experiments and Multiple Regression. Apart from these new features, the users get access to the regular analysis methods like capability analysis hypothesis chart and control charts. Minitab 17 has gained acceptance around the globe, and for the same reason, the company has launched the product in various regional languages like French, English, German, Spanish and Chinese. The prompt customer support system is the backbone of the success story of Minitab 17.



5. R software

R is a termed as an open source programming language along with being software. It is specially designed for the statistical analysis of data along with providing graphical interpretations that are supported by R foundations only. It was developed with the motive of providing free availability of statistical analysis tool. It is an open source language and software that means it can be used to develop statistical tools along with providing them itself. It is mainly a command based software and less of GUI that makes it a bit tough to use. Thus, it is less popular these days as long codes are required to execute the statistical analysis and consumes time. However, for those who have a passion for programming in statistics, R acts as a blessing in disguise. It is possible for them to play with numbers and figures.



6. SAS (Statistical Analysis Software)

SAS is a statistical analysis platform that offers options to use either the GUI, or to create scripts for more advanced analyses. It is a premium solution that is widely used in business, healthcare, and human behavior research alike. It’s possible to carry out advanced analyses and produce publication-worthy graphs and charts, although the coding can also be a difficult adjustment for those not used to this approach.



Thus, all these tools have their unique features in form to produce the best results for any of the statistical data entered by the user. Some are command based while others have GUI, but the main motto is to get unified and accurate result in any situation.

POISSON DISTRIBUTION USING MOMENT GENERATING FUNCTIONS

Moment generating functions

If X is a random variable, then its moment generating function is

Recall that                                                                                            

Exponential series

Therefore, expectation of X (Ex) =

For poisson

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What Makes a Normal Distribution Normal?

Good question...

What makes 98.60 degrees normal?

What makes people normal?



Generally, references to a statistical distribution or just a "distribution" mean a "frequency distribution." That is, what is the number of times or the frequency with which each value in the distribution occurs.



As it turns out, a large percent of all frequency distributions meet the same set of criteria. Such distributions are called "normal." A more popular term is "bell curve."



NOTE: "Bell" is not a technical term. However, because the term stuck, for convenience it is used in this series.



These normal types of distributions have many uses in market research and other statistical applications. A lot of statistical theory that applies to market research assumes normal distributions.



Examples of normal distributions in humans include: height; weight; test scores especially for standardized tests such as I.Q.; and various abilities, traits, tastes, and preferences. All assume a large number of people being "measured." One notable exception is income earned, which will be discussed in the next article with distributions that are not normal.



Normal distributions also are common in both nature and business. For example, light bulb packages have information on the number of hours the bulb should last, the watts (energy used), and the lumens (light output).



Each of those numbers is an arithmetic mean of the frequency distribution generated by testing large numbers of light bulbs. Each of those distributions is bell-shaped or normal.



So what are the criteria for a distribution to be normal?



1) The distribution is unimodal (only one most frequently occurring value).

2) The arithmetic mean, the mode, and the median are all the same value. That value is the value representing the highest point on the distribution;

3) The distribution is bi-laterally symmetrical.

BY WHAT?!

Bi-laterally symmetrical means the left half is a mirror image of the right half (unless you're left-handed, then the right half is a mirror image of the left half).

4) One standard deviation--hereafter noted as 1�OE --measured each way from the arithmetic mean (what's referred to as plus or minus one standard deviation or � 1�OE) represents slightly over 68 percent of all the values in the distribution. � 1.96 �OEs represents the middle 95 percent of the values. You can go to readily available tables to see how many standard deviations from the mean are associated with what percent of all the values in the distribution. This percent is often referred to as the "area under the curve." For instance, � 1�OE covers slightly over 68 percent of the area under the curve. The curve is the graphic representation of the frequency distribution.

and

5) There are some other criteria, but the above ones are the main ones (at least for now).



Normal distributions come in various sizes and shapes but all meet the criteria noted above. Some normal distributions look like they are relatively short and spread out; other normal distributions look relatively tall and thin. The largest percent of all normal distributions are in between those more extreme shapes and are the true bell curves.



In market research, you might want to ask consumers how they would rate the service they received. A properly designed survey would gives choices such as "excellent" "good" "fair" "poor" "very poor." A future article will deal with the problems of such surveys. The point here is that the choices have to be symmetrical in terms of balancing the choices around the middle of the distribution. The results should produce a normal distribution. If the results are not "normally distributed" you should be suspicious of the results. Contrary to what many are led to think, not everything is good or excellent.