what mean the SPSS IN STATISTICS?
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SPSS is a computer program (originally, Statistical Package for the Social Sciences) \n\nIt is among the most widely used programs for statistical analysis.
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(m)\n\nBusiness statistics is the science of good decision making in the face of uncertainty and is used in many disciplines such as financial analysis, econometrics, auditing, production and operations including services improvement, and marketing research. These sources feature regular repetitive publication of series of data. This makes the topic of time series especially important for business statistics. It is also a branch of applied statistics working mostly on data collected as a by-product of doing business or by government agencies. It provides knowledge and skills to interpret and use statistical techniques in a variety of business applications. A typical business statistics course is intended for business majors, and covers statistical study, descriptive statistics (collection, description, analysis, and summary of data), probability, and the binomial and normal distributions, test of hypotheses and confidence intervals, linear regression, and correlation.
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Everywhere. Statistics as a science is, generally speaking, the art of using samples to estimate the truth about the whole. SInce we are always trying to figure out answers about the world, predicting the future and understanding the past - like weather patterns, human behavior, lottery results, health outcomes etc... we use statistics. \n\nFor example: if we want to know how popular the president is we can do the following:\n1. Ask everyone in the US what they think of the president.\n2. Take a sample of people and use their answer as a "good guess" regarding how the rest of the people would have answered.\n\nOption 1 would take wayyyyyy too long. Option 2, if executed properly, could get a pretty close guess as to the % of people who liked/didn't like the president. SInce we are never 100$ sure about our guesses in statistics, we always have a margin of error (in surveys they say + or - 3% for instance. That's because the answer is based on a statistical guess, not every person in the US answering).
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I'm assuming you mean statistics if so here's a few links\nhttp://www.infoplease.com/spot/stpatsday1.html\nhttp://www.census.gov/Press-Release/www/releases/archives/facts_for_features/001687.html
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Regression analysis is very complicated mathematical/statistic analysis that is very difficult to describe easily.  R-squared is a measure of how closely an investment tracks the S&P 500 or other index.  While I am not a great fan of investopedia.com, they give some answers in this case.\n(These comments refer to investment analysis, regression analysis is also used in other fields.)
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If you are referring to validity, do a principal components analysis.  Reliability use Cronbach's alpha.  Cross reference your results from PCA with Cluster Analysis.  I am a sas user so I only no the code for sas which is:\n\nproc factor data=females\nsimple\nmethod=prin\npriors=one\nmineigen=1\nscree\nrotate=varimax\nround\nflag=.5;\nvar rate1-rate10;\nrun;\n\nRobert DeVellis; Scale Development: Theory and Application 2nd edition.
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They are both pretty powerfull analysis packages. SPSS is cheaper and SAS is better on functionality.  This article may be very useful considering you are looking for answers in marketing analytics:\n\nhttp://marketing-and-technology.blogspot.com/2006/05/sas-vs-spss.html
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Statistics Canada is the federal government's statistics department.  Good luck.
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Does your school give you access to SPSS?\n\nCheck with one of the librarians at your campus library....they can really help you out with this type of stuff.\n\nGood Luck!
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A statistic used as a measure of the dispersion or variation in a distribution. It is equal to the square root of the arithmetic mean of the squares of the deviations from the arithmetic mean. Simply put, standard deviation measures how spread out the values in a data set are. More precisely, it is a measure of the average difference between the values of the data in the set. If the data points are all similar, then the standard deviation will be low (closer to zero). If the data points are highly variable, then the standard variation is high (further from zero). the greater the standard deviation, the higher the risk. it is always positive, and NEVER negative. the formula you use is....well i can't write it because i don't have the symbols on my keyboard, but i'll try:\n\n\nσ= √(Σ[D-E]^2P)\n\nwhere:\nσ=sigma=standard deviation\nΣ=capital sigma= the sum of\nD=outcome\nE=expected value\n^2= squared\nP= Probability\n√=square root\n\nhere is an example:\n\n(Assumptions)(Outcome probability)(Outcomes)\n(Pessimistic)(0.2)                     (300)\n(Successful)(0.6)                     (600)\n(Optimistic)(0.2)                     (900)\n\n(sorry, the table won't keep the spaces, so i put brackets in)\n\nok, you need the expected value, which is the sum of all of the outcomes, times their probabilities, like so:\nexpected value = 300×0.2+600×0.6+900×0.2 = 600\n\n\nthen standard deviation would be calculated like so:\nstandard deviation = {(300-600)2×0.2+(600-600)2×0.6+(900-600)2×0.2}½ = 190\n\nhope that helped! oh, and if you don't understand, the "to the power of 1/2" part is the same as taking the square root.
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SPSS\nWith your data entered, go to ANALYZE > GENERAL LINEAR MODEL > UNIVARIATE \nEnter dependent variable in Dependent List \nEnter independent variables in Factor \nContinue – OK \nOutput:\n(A) Descriptives (N, Mean, Std. Dev., etc) \nThis will give you a table. On the right hand side, the significances will be listed, along with the F values. On the far left side, under the column “source,” your variables will be listed. The corresponding F values and significances are for main effects and interaction effects. If the significance reading is less than .05, you are able to reject the null hypothesis.
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in order to do statistics you need data\n\nie.  we need number to do this
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I doubt that you can.  Use MINTAB or SPSS.
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Statistical programming language ... runs on PC, Unix and Mainframe (similar to SAS).\n\nSPSS = Statistical Package for the Social Sciences.\n\nSAS (industry leader) ... Statistical Application Software.
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Principal components analysis is a statistical technique to find the important variables (or linear combination of variables) in a set of data.\n\nYou need a specialised computer program to solve practical problems, but a good tutorial can be found here:\n\nhttp://csnet.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf
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Oh.... wait till I get home! Than I will edit this and give you the answer you need. I am at work now, so I do not have SPSS to rely on....
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Standard Deviation is a simple measure of how much a list of numbers varies. It quickly tells you how much deviation there is from the average.\n\nThink of the familiar bell curve, the so-called normal curve. It might show how tall students are in your school\n\nAbout 68% of the students will have heights between the 1 standard deviation mark on either side of the central peak -- 34% on the left, and 34% on the right.\n\n68.26% of the area under the curve is within one standard deviation of the mean.\n\n95.45% of the area is within two standard deviations.\n\n99.73% of the area is within three standard deviations.\n\n99.99% of the area is within four standard deviations.\n\nIt is a quick way to explain a large hunk of data!\n\nSo for instance if one standard deviation in your school height list is 1 inch, then you'll know that 68 out of hundred kids are within 1 inch of the central value.