Casio FX 1.0 PLUS инструкция обслуживания

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Хорошее руководство по эксплуатации

Законодательство обязывает продавца передать покупателю, вместе с товаром, руководство по эксплуатации Casio FX 1.0 PLUS. Отсутствие инструкции либо неправильная информация, переданная потребителю, составляют основание для рекламации в связи с несоответствием устройства с договором. В законодательстве допускается предоставлении руководства в другой, чем бумажная форме, что, в последнее время, часто используется, предоставляя графическую или электронную форму инструкции Casio FX 1.0 PLUS или обучающее видео для пользователей. Условием остается четкая и понятная форма.

Что такое руководство?

Слово происходит от латинского "instructio", тоесть привести в порядок. Следовательно в инструкции Casio FX 1.0 PLUS можно найти описание этапов поведения. Цель инструкции заключается в облегчении запуска, использования оборудования либо выполнения определенной деятельности. Инструкция является набором информации о предмете/услуге, подсказкой.

К сожалению немного пользователей находит время для чтения инструкций Casio FX 1.0 PLUS, и хорошая инструкция позволяет не только узнать ряд дополнительных функций приобретенного устройства, но и позволяет избежать возникновения большинства поломок.

Из чего должно состоять идеальное руководство по эксплуатации?

Прежде всего в инструкции Casio FX 1.0 PLUS должна находится:
- информация относительно технических данных устройства Casio FX 1.0 PLUS
- название производителя и год производства оборудования Casio FX 1.0 PLUS
- правила обслуживания, настройки и ухода за оборудованием Casio FX 1.0 PLUS
- знаки безопасности и сертификаты, подтверждающие соответствие стандартам

Почему мы не читаем инструкций?

Как правило из-за нехватки времени и уверенности в отдельных функциональностях приобретенных устройств. К сожалению само подсоединение и запуск Casio FX 1.0 PLUS это слишком мало. Инструкция заключает ряд отдельных указаний, касающихся функциональности, принципов безопасности, способов ухода (даже то, какие средства стоит использовать), возможных поломок Casio FX 1.0 PLUS и способов решения проблем, возникающих во время использования. И наконец то, в инструкции можно найти адресные данные сайта Casio, в случае отсутствия эффективности предлагаемых решений. Сейчас очень большой популярностью пользуются инструкции в форме интересных анимаций или видео материалов, которое лучше, чем брошюра воспринимаются пользователем. Такой вид инструкции позволяет пользователю просмотреть весь фильм, не пропуская спецификацию и сложные технические описания Casio FX 1.0 PLUS, как это часто бывает в случае бумажной версии.

Почему стоит читать инструкции?

Прежде всего здесь мы найдем ответы касательно конструкции, возможностей устройства Casio FX 1.0 PLUS, использования отдельных аксессуаров и ряд информации, позволяющей вполне использовать все функции и упрощения.

После удачной покупки оборудования/устройства стоит посвятить несколько минут для ознакомления с каждой частью инструкции Casio FX 1.0 PLUS. Сейчас их старательно готовят или переводят, чтобы они были не только понятными для пользователя, но и чтобы выполняли свою основную информационно-поддерживающую функцию.

Содержание руководства

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    ALGEBRA FX 2.0 PLUS FX 1.0 PLUS User’s Guide 2 ( Additional Functions ) E http://world.casio.com/edu_e/[...]

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    CASIO ELECTRONICS CO ., L TD . Unit 6, 1000 North Circular Road, London NW2 7JD, U.K. Important! Please k eep your manual and all inf ormation handy for future ref erence.[...]

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    20010101 ••• ••••• •••• ••••• •• • ••••• ••••• ••••• ••• ••••• ••••• •••• ••••• ••• ••••• ••••• ••••• • •• ••••• •••• ••••• ••• ••••• ••••• [...]

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    20010101 Contents Chapter 1 Ad vanced Statistics Application 1-1 Adv anced Statistics (ST A T) .............................................................. 1-1-1 1-2 T ests (TEST) .................................................................................... 1-2-1 1-3 Confidence Interval (INTR) ..............................................[...]

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    20010101 Adv anced Statistics Application 1-1 Ad vanced Statistics (ST A T) 1-2 T ests (TEST) 1-3 Confidence Interval (INTR) 1-4 Distribution (DIST) 1 Chapter[...]

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    20010101 1-1 Adv anced Statistics (ST A T) u u u u u Function Menu The follo wing shows the function menus for the ST A T Mode list input screen. Pressing a function key that corresponds to the added item displays a menu that lets you select one of the functions listed below . • 3 (TEST) ... T est (page1-2-1) • 4 (INTR) ... Confidence interval [...]

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    20010101 • Logar ithmic Reg ression ... MSE = Σ 1 n – 2 i =1 n ( y i – ( a + b ln x i )) 2 •E xponential Repression ... MSE = Σ 1 n – 2 i =1 n ( ln y i – ( ln a + bx i )) 2 •P ow er Regression ... MSE = Σ 1 n – 2 i =1 n ( ln y i – ( ln a + b ln x i )) 2 •S in Reg ression ... MSE = Σ 1 n – 2 i =1 n ( y i – ( a sin ( bx i [...]

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    20010101 4. After you are finished, press i to clear the coordinate values and the pointer from the displa y . · The pointer does not appear if the calculated coordinates are not within the display range. ·T he coordinates do not appear if [Off] is specified for the [Coord] item of the [SETUP] screen. · The Y -CAL function can also be used with [...]

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    20010101 u u u u u Common Functions • The symbol “ ■ ” appears in the upper right cor ner of the screen while e xecution of a calculation is being performed and while a graph is being drawn. Pressing A during this time terminates the ongoing calculation or draw operation (AC Break). • Pressing i or w while a calculation result or graph is[...]

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    20010101 1-2 T ests (TEST) The Z T est pro vides a var iety of diff erent standardization-based tests. The y mak e it possib le to test whether or not a sample accurately represents the population when the standard deviation of a population (such as the entire population of a country) is known from previous tests. Z testing is used f or market rese[...]

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    20010101 The following pages e xplain various statistical calculation methods based on the principles descr ibed abov e . Details concer ning statistical principles and terminology can be found in any standard statistics textbook. On the initial ST A T Mode screen, press 3 (TEST) to display the test men u, which contains the following items. • 3 [...]

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    20010101 Pe rf or m the f ollowing key operations from the statistical data list. 3 (TEST) b (Z) b (1-Smpl) The following shows the meaning of each item in the case of list data specification. Data ............................ data type µ .................................. population mean v alue test conditions (“ G µ 0 ” specifies two-tail t[...]

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    20010101 Calculation Result Output Example µ G 11.4 ........................ direction of test z .................................. z score p .................................. p-value o .................................. mean of sample x σ n -1 ............................. sample standard deviation (Displayed only f or Data: List setting.) n ..[...]

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    20010101 u u u u u 2-Sample Z T est This test is used when the standard deviations f or tw o populations are known to test the h ypothesis . The 2-Sample Z T est is applied to the normal distr ib ution. Z = o 1 – o 2 σ n 1 1 2 σ n 2 2 2 + o 1 : mean of sample 1 o 2 : mean of sample 2 σ 1 : population standard deviation of sample 1 σ 2 : popul[...]

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    20010101 o 1 ................................. mean of sample 1 n 1 ................................. siz e (positive integer) of sample 1 o 2 ................................. mean of sample 2 n 2 ................................. siz e (positive integer) of sample 2 After setting all the parameters, align the cursor with [Execute] and then press [...]

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    20010101 u u u u u 1-Prop Z T est This test is used to test for an unknown proportion of successes. The 1-Prop Z T est is applied to the normal distr ibution. Z = n x n p 0 (1– p 0 ) – p 0 p 0 : e xpected sample proportion n : s i z e of sample Pe rf or m the f ollowing key operations from the statistical data list. 3 (TEST) b (Z) d (1-Prop) Pr[...]

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    20010101 u u u u u 2-Prop Z T est This test is used to compare the propor tion of successes. The 2-Prop Z T est is applied to the nor mal distribution. Z = n 1 x 1 n 2 x 2 – p (1 – p ) n 1 1 n 2 1 + x 1 : data value of sample 1 x 2 : data value of sample 2 n 1 : s i z e of sample 1 n 2 : s i z e of sample 2 ˆ p : estimated sample propor tion P[...]

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    20010101 p 1 > p 2 ............................ direction of test z .................................. z score p .................................. p-value ˆ p 1 ................................. estimated propor tion of sample 1 ˆ p 2 ................................. estimated propor tion of sample 2 ˆ p .................................. e[...]

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    20010101 k k k k k t T ests u u u u u t T est Common Functions Y ou can use the f ollowing graph analysis functions after dr a wing a g r aph. • 1 (T) ... Displa ys t score . Pressing 1 (T) di spla ys the t score at the bottom of the display , and displa ys the pointer at the corresponding location in the graph (unless the location is off the gra[...]

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    20010101 u u u u u 1-Sample t T est This test uses the hypothesis test for a single unkno wn population mean when the population standard deviation is unkno wn. The 1-Sample t T est is applied to t -distr ib ution. t = o – 0 µ σ x n –1 n o : mean of sample µ 0 : assumed population mean x σ n -1 : sample standard deviation n : s i z e of sam[...]

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    20010101 Calculation Result Output Example µ G 11.3 ...................... direction of test t ................................... t score p .................................. p-value o .................................. mean of sample x σ n -1 ............................. sample standard deviation n .................................. size of sa[...]

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    20010101 u u u u u 2-Sample t T est 2-Sample t T est compares the population means when the population standard deviations are unknown. The 2-Sample t T est is applied to t -distribution. The following applies when pooling is in eff ect. t = o 1 – o 2 n 1 1 + n 2 1 x p n –1 2 σ x p n –1 = σ n 1 + n 2 – 2 ( n 1 –1) x 1 n –1 2 +( n 2 ?[...]

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    20010101 The following shows the meaning of each item in the case of list data specification. Data ............................ data type µ 1 ................................. sample mean v alue test conditions (“ G µ 2 ” specifies two-tail test, “< µ 2 ” specifies one-tail test where sample 1 is smaller than sample 2, “> µ 2 ?[...]

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    20010101 Calculation Result Output Example µ 1 G µ 2 ........................... direction of test t ................................... t score p .................................. p-value df ................................. degrees of freedom o 1 ................................. mean of sample 1 o 2 ................................. mean of s[...]

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    20010101 u u u u u LinearReg t T est LinearReg t T est treats paired-v ar iab le data sets as ( x , y ) pairs , and uses the method of least squares to deter mine the most appropriate a , b coefficients of the data for the regression f or mula y = a + bx . It also determines the correlation coefficient and t value , and calculates the e xtent of th[...]

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    20010101 Calculation Result Output Example β G 0 & ρ G 0 .............. direction of test t ................................... t score p .................................. p-value df ................................. degrees of freedom a .................................. constant ter m b .................................. coefficient s ....[...]

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    20010101 k k k k k χ 2 T est χ 2 T est sets up a n umber of independent groups and tests h ypothesis related to the propor tion of the sample included in each group . The χ 2 T est is applied to dichotomous variab les (var iab le with tw o possible values , such as yes/no). Expected counts F ij = Σ x ij i =1 k × Σ x ij j =1 k ΣΣ i =1 j =1 x[...]

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    20010101 After setting all the parameters, align the cursor with [Execute] and then press one of the function k e ys shown below to perf orm the calculation or dr a w the g r aph. • 1 (CALC) ... P erforms the calculation. • 6 (DRA W) ... Draws the g r aph. Calculation Result Output Example χ 2 ................................. χ 2 val ue p ..[...]

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    20010101 k k k k k 2-Sample F T est 2-Sample F T est tests the h ypothesis for the ratio of sample variances . The F T est is applied to the F distr ibution. F = x 1 n –1 2 σ x 2 n –1 2 σ Pe rf or m the f ollowing key operations from the statistical data list. 3 (TEST) e (F) The following is the meaning of each item in the case of list data s[...]

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    20010101 After setting all the parameters, align the cursor with [Execute] and then press one of the function k e ys shown below to perf orm the calculation or dr a w the g r aph. • 1 (CALC) ... P erf or ms the calculation. • 6 (DRA W) ... Draws the g r aph. Calculation Result Output Example σ 1 G σ 2 .......................... direction of t[...]

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    20010101 k k k k k ANO V A ANO V A tests the hypothesis that the population means of the samples are equal when there are multiple samples. One-W ay ANO V A is used when there is one independent v ar iable and one dependent variab le . Two - Wa y ANOV A is used when there are tw o independent variab les and one dependent variab le . Pe rf or m the [...]

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    20010101 Calculation Result Output Example One-W ay ANO V A Line 1 (A) .................... Factor A df valu e, SS val ue , MS valu e, F value , p-value Line 2 (ERR) ............... Error df va lu e, SS val ue, MS va lue Tw o - W a y ANO V A Line 1 (A) .................... Factor A df valu e, SS val ue , MS valu e, F value , p-value Line 2 (B) ....[...]

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    20010101 k k k k k ANO V A (T w o-W a y) u u u u u Description The nearby tab le shows measurement results f or a metal product produced by a heat treatment process based on two treatment levels: time (A) and temper ature (B). The e xperiments were repeated twice each under identical conditions . Pe rf or m analysis of v ar iance on the f ollo wing[...]

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    20010101 u u u u u Input Example u u u u u Results 1-2-25 T ests (TEST)[...]

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    20010101 1-3 Confidence Interval (INTR) A confidence inter v al is a r ange (interv al) that includes a statistical value, usually the population mean. A confidence inter v al that is too broad makes it difficult to get an idea of where the population value (true value) is located. A narro w confidence inter val, on the other hand, limits the popul[...]

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    20010101 u u u u u General Confidence Interval Precautions Inputting a value in the range of 0 < C-Level < 1 for the C-Le vel setting sets you value y ou input. Inputting a v alue in the r ange of 1 < C-Lev el < 100 sets a value equiv alent to your input divided by 100. # Inputting a value of 100 or greater , or a negative value causes [...]

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    20010101 k k k k k Z Interval u u u u u 1-Sample Z Interval 1-Sample Z Interval calculates the confidence inter val f or an unknown population mean when the population standard deviation is kno wn. The following is the confidence interval. Left = o – Z α 2 σ n Right = o + Z α 2 σ n Ho w e ver , α is the le vel of significance. The value 100 [...]

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    20010101 After setting all the parameters, align the cursor with [Execute] and then press the function key shown belo w to perform the calculation. • 1 (CALC) ... P erforms the calculation. Calculation Result Output Example Left .............................. inter v al lower limit (left edge) Right ............................ inter v al upper l[...]

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    20010101 The following shows the meaning of each item in the case of list data specification. Data ............................ data type C-Le vel ........................ confidence level (0 < C-Lev el < 1) σ 1 ................................. population standard de viation of sample 1 ( σ 1 > 0) σ 2 ................................. [...]

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    20010101 u u u u u 1-Prop Z Interv al 1-Prop Z Interval uses the n umber of data to calculate the confidence inter val f or an unknown propor tion of successes. The following is the confidence interval. The v alue 100 (1 – α ) % is the confidence le vel. Left = – Z α 2 Right = + Z x n n 1 n x n x 1 – x n α 2 n 1 n x n x 1 – n :s i z e of[...]

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    20010101 u u u u u 2-Prop Z Interval 2-Prop Z Interval uses the n umber of data items to calculate the confidence interval for the defference between the proportion of successes in two populations. The following is the confidence interval. The v alue 100 (1 – α ) % is the confidence le vel. Left = – – Z α 2 x 1 n 1 x 2 n 2 n 1 n 1 x 1 1– [...]

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    20010101 Left .............................. inter v al lower limit (left edge) Right ............................ inter v al upper limit (r ight edge) ˆ p 1 ................................. estimated sample propotion for sample 1 ˆ p 2 ................................. estimated sample propotion for sample 2 n 1 ................................[...]

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    20010101 o .................................. mean of sample x σ n -1 ............................. sample standard deviation ( x σ n -1 > 0) n .................................. size of sample (positive integer) After setting all the parameters, align the cursor with [Execute] and then press the function key shown belo w to perform the calcul[...]

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    20010101 The following confidence interv al applies when pooling is not in effect. The v alue 100 (1 – α ) % is the confidence le vel. Left = ( o 1 – o 2 )– t df α 2 Right = ( o 1 – o 2 )+ t df α 2 + n 1 x 1 n –1 2 σ n 2 x 2 n –1 2 σ + n 1 x 1 n –1 2 σ n 2 x 2 n –1 2 σ C = df = 1 C 2 n 1 –1 + (1 – C ) 2 n 2 –1 + n 1 x 1[...]

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    20010101 o 1 ................................. mean of sample 1 x 1 σ n -1 ............................ standard deviation ( x 1 σ n -1 > 0) of sample 1 n 1 ................................. size (positive integer) of sample 1 o 2 ................................. mean of sample 2 x 2 σ n -1 ............................ standard deviation ( x[...]

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    20010101 1-4 Distrib ution (DIST) There is a variety of diff erent types of distr ibution, b ut the most well-known is “normal distr ib ution, ” which is essential f or perfor ming statistical calculations. Nor mal distribution is a symmetr ical distribution centered on the g reatest occurrences of mean data (highest frequency), with the freque[...]

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    20010101 u u u u u Common Distribution Functions After drawing a graph, you can use the P-CAL function to calculate an estimated p-value for a par ticular x va lu e. The following is the general procedure f or using the P-CAL function. 1. After dr awing a graph, press 1 (P-CAL) to display the x value input dialog bo x. 2. Input the v alue you want [...]

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    20010101 k k k k k Normal Distribution u u u u u Normal Probability Density Nor mal probability density calculates the probability density of nomal distribution from a specified x value. Nor mal probability density is applied to standard nor mal distribution. πσ 2 f ( x ) = 1 e – 2 2 σ ( x – µ ) 2 µ ( σ > 0) Pe rf or m the f ollowing k[...]

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    20010101 u u u u u Normal Distribution Pr obability Nor mal distrib ution probability calculates the probability of nor mal distribution data f alling between two specific values. πσ 2 p = 1 e – dx 2 2 σ ( x – µ ) 2 µ a b ∫ a : lo w er boundar y b : upper boundar y Pe rf or m the f ollowing key operations from the statistical data list. [...]

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    20010101 Calculation Result Output Example p .................................. nor mal distribution probability z:Low ........................... z:Low value (con ver ted to standardize z score for lower value) z:Up ............................. z:Up value (conv er ted to standardize z score for upper v alue) u u u u u In verse Cumulative Normal D[...]

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    20010101 After setting all the parameters, align the cursor with [Execute] and then press the function key shown belo w to perform the calculation. • 1 (CALC) ... P erforms the calculation. Calculation Result Output Examples x ....................................... inverse cum ulativ e nor mal distr ibution (T ail:Left upper boundar y of integ r[...]

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    20010101 k k k k k Student- t Distribution u u u u u Student- t Pr obability Density Student- t probability density calculates t probability density from a specified x va lu e. f ( x ) = Γ Γ df π – df + 1 2 2 df 2 df + 1 df x 2 1+ Pe rf or m the f ollowing key operations from the statistical data list. 5 (DIST) c (T) b (P .D) Data is specified[...]

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    20010101 u u u u u Student- t Distribution Pr obability Student- t distrib ution probability calculates the probability of t distr ib ution data f alling between two specific values. p = Γ Γ df π 2 df 2 df + 1 – df +1 2 df x 2 1+ dx a b ∫ a :l ow er boundar y b : upper boundary Pe rf or m the f ollowing key operations from the statistical da[...]

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    20010101 Calculation Result Output Example p .................................. Student- t distrib ution probability t:Lo w ........................... t:Low v alue (input lower v alue) t:Up ............................. t:Up v alue (input upper v alue) k k k k k χ 2 Distribution u u u u u χ 2 Pr obability Density χ 2 probability density calcula[...]

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    20010101 Calculation Result Output Example p .................................. χ 2 probability density # Current V -Window settings are used f or graph drawing when the SET UP screen's [Stat Wind] setting is [Manual]. The V - Window settings below are set automatically when the [Stat Wind] setting is [A uto]. Xmin = 0, Xmax = 11.5, Xscale = [...]

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    20010101 u u u u u χ 2 Distrib ution Probability χ 2 distribution probability calculates the probability of χ 2 distribution data falling betw een two specific values. p = Γ 1 2 df df 2 x e dx 2 1 df 2 –1 x 2 – a b ∫ a :l ow er boundar y b : upper boundary Pe rf or m the f ollowing key operations from the statistical data list. 5 (DIST) d[...]

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    20010101 Calculation Result Output Example p .................................. χ 2 distribution probability k k k k k F Distrib ution u u u u u F Probability Density F probability density calculates the probability density function f or the F distr ib ution at a specified x va lu e. Γ n 2 x d n n 2 – 1 2 n Γ 2 n + d Γ 2 d d nx 1 + n + d 2 f [...]

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    20010101 Calculation Result Output Example p .................................. F probability density # V-Windo w settings f or graph dr awing are set automatically when the SET UP screen's [Stat Wind] setting is [A uto]. Current V - Window settings are used for graph drawing when the [Stat Wind] setting is [Manual]. 1-4-13 Distribution (DIST)[...]

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    20010101 u u u u u F Distribution Pr obability F distribution probability calculates the probability of F distr ib ution data falling between two specific values. p = Γ n 2 dx x d n n 2 –1 2 n Γ 2 n + d Γ 2 d d nx 1 + n + d 2 – a b ∫ a : lower boundary b : upper boundar y Pe rf or m the f ollowing key operations from the statistical data l[...]

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    20010101 Calculation Result Output Example p .................................. F distribution probability 1-4-15 Distribution (DIST)[...]

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    20010101 k k k k k Binomial Distribution u u u u u Binomial Probability Binomial probability calculates a probability at a specified value for the discrete binomial distr ib ution with the specified number of tr ials and probability of success on each trial. f ( x ) = n C x p x (1– p ) n – x ( x = 0, 1, ·······, n ) p : success probabili[...]

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    20010101 Calculation Result Output Example p .................................. binomial probability u u u u u Binomial Cumulative Density Binomial cumulative density calculates a cumulative probability at a specified v alue f or the discrete binomial distribution with the specified number of tr ials and probability of success on each tr ial. Pe rf[...]

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    20010101 After setting all the parameters, align the cursor with [Execute] and then press the function key shown belo w to perform the calculation. • 1 (CALC) ... P erforms the calculation. Calculation Result Output Example p ......................................... probability of success 1-4-18 Distribution (DIST) 20011101[...]

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    20010101 k k k k k Po isson Distribution u u u u u Po isson Probability Po isson probability calculates a probability at a specified value for the discrete P oisson distribution with the specified mean. f ( x ) = x! e – x µ µ ( x = 0, 1, 2, ···) µ :m ean ( µ > 0) Pe rf or m the f ollowing key operations from the statistical data list. 5[...]

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    20010101 u u u u u P oisson Cumulative Density Po isson cumulativ e density calculates a cumulativ e probability at specified value for the discrete Poisson distribution with the specified mean. Pe rf or m the f ollowing key operations from the statistical data list. 5 (DIST) g (P oissn) c (C .D) The following shows the meaning of each item when da[...]

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    20010101 k k k k k Geometric Distrib ution u u u u u Geometric Probability Geometr ic probability calculates the probability at a specified v alue, and the number of the trial on which the first success occurs, for the geometr ic distrib ution with a specified probability of success. f ( x ) = p (1– p ) x – 1 ( x = 1, 2, 3, ···) Pe rf or m t[...]

  • Страница 67

    20010101 u u u u u Geometric Cumulative Density Geometr ic cumulativ e density calculates a cumulative probability at specified value , the nu mber of the trial on which the first success occurs, f or the discrete geometr ic distr ib ution with the specified probability of success. Pe rf or m the f ollowing key operations from the statistical data [...]