000			03587cam a2200385 i 4500
001			20617734
003			NU
005			20240229145955.0
008			180806t20182018nyua 001 0 eng
010			_a 2018037190
020			_a978-1--5072-0817-5
040			_aDLC _beng _cDLC _erda _dDLC
042			_apcc
050	0	0	_aQA 276.12 .B67 2018
082	0	0	_a519.5 _223
100	1		_aBorman, David, _eauthor.
245	1	0	_aStatistics 101 : _bfrom data analysis and predictive modeling to measuring distribution and determining probability, your essential guide to statistics / _cDavid Borman.
250			_aFirst Adams media hardcover edition.
260			_aNew York : _bAdams Media, _cc2018.
300			_a235 pages : _billustrations (some color) ; _c19 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
365			_b716
490	0		_aAdams 101
500			_aA crash course in statistics"--Cover.
504			_aIncludes index.
505			_aThe basics of statistics -- How statistics are used -- Key points of statistical analytics -- Mixing up the test -- Knowing the quality of your data -- Modeling risk, measuring samples, and predicting -- Frequency distributions -- Dot plots, bar charts, histograms, frequency polygons -- More ways to see numbers-based data -- The mean, the median, and the mode -- The range and interquartile range -- Mean deviations and variations -- The law of large numbers -- Empirical probability and subjective probability -- Yes or no -- Basics of probability distributions -- Analyzing probability distributions -- The roll of the dice -- Normal distribution -- The central limit theorem -- Outliers on the bell curve -- Limited and unlimited data -- Variance as a measure of risk -- Size matters -- Measuring distribution -- What are confidence intervals? -- Measuring confidence intervals -- The basics of hypothesis testing -- Taking it to the next level -- Measuring large sample population proportions -- The hypothesis test -- Patterns in data -- Predicting the future -- The T-distribution -- Groups of data -- Tests for two populations -- Statistics in academic research -- Getting good data -- A regression example -- What regression data tables tell us -- Determining the causes -- Chi-square distribution -- Anova basics -- Anova at work -- Quantitative research design -- Quality of the data -- Quantity and sourcing of the data -- Appropriate survey design -- The ethics of statistics -- Big data, supercomputers, and artificial intelligence.
520			_aFrom understanding the percentage probability that it will rain later today, to evaluating your risk of a health problem, or the fluctuations in the stock market, statistics impact our lives in a variety of ways, and are vital to a variety of careers and fields of practice. Unfortunately, most statistics text books just make us want to take a snooze, but with Statistics 101, you'll learn the basics of statistics in a way that is both easy-to-understand and apply. From learning the theory of probability and different kinds of distribution concepts, to identifying data patterns and graphing and presenting precise findings, this essential guide can help turn statistical math from scary and complicated, to easy and fun.-- _cProvided by publisher.
650		0	_aSTATISTICS.
650		0	_aMATHEMATICAL STATISTICS.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2lcc _cBK _n0
999			_c4502 _d4502