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l = [0,1,2,3] l = range(4) # [0,1,2,3]

#REDIRECT [[Nato Architecture Framework (NAF) - 4 1 of 5 - NATO Meta Model - Elements Defintions]]

A basic property of Pearson's r is that its possible range is from -1 to 1. * A correlation of -1 means a perfect negative linear relationship,

...ents of the same type. This is useful for sorting. cmp() returns -1, 0, or 1. d = {1:'A', 2:'B'}

* The results were (10,20,30) before the change and (1,2,3,4,5) after the change * The results were pre: (1,21,31,29) post: (1,2,3,4,5)

< [[Power Demo 1]] | [[Factors Affecting Power]] >

Pearson's r can range from -1 to 1. * r = 1 indicates a perfect positive linear relationship between variables

== NTV-1 Technical Standards Profile。 == NTV-1 defines the technical and non-technical standards, guidance and policy appl

A normal distribution with a mean of 0 and a standard deviation of 1 * Since the distribution has a mean of 0 and a standard deviation of 1, the Z column is equal to the number of standard deviations below (or above

1. Show the difference between 2012-01-01 and 12-12323

A 0 0 1 1 0 0 0 0 0 0 2 B 1 0 1 1 0 0 0 0 0 0 3

for (var i=1; i<=1000000; i++) { "score" : Math.floor(Math.random()*10+1),

for i in $(seq 10) ; do echo "# round 1 $i" >> code.sh ; git commit -a -m "c$i" ; done echo "exit 1" > code.sh

== Step 1: State the Null Hypothesis == * A typical null hypothesis is μ1 - μ2 = 0 which is equivalent to μ1 = μ2

== NPV-1, Programme Portfolio Relationships。 == The Programme Portfolio Relationships Subview (NPV-1) details the relationships among projects within a major NATO programme, su

$ docker swarm join --token SWMTKN-1-3nt...sfe 10.0.2.10:2377 $ docker service create --replicas 1 --name training kamilbaran/nobleprog_training:training_app_v1

<div>1</div>

create table salgrade (grade int(1), losal int(4), hisal int(4)); insert into salgrade values (1, 700, 1200), (2, 1201, 1400), (3, 1401, 2000), (4, 2001, 3000), (5, 3001, 9

...in satisfaction level (SAT) over four training sessions (training-Quarter 1 or TQ1, etc.) for 20 unemployed men and women undergoing quarterly training s <- rbind(s,cbind(Gender,Sat=TQ1,Quarter="1"))

-a = 1 * 2 -2 = 1 + 1

== Exercise 1⌘ == Rewrite the exercise 1 using ''accumulate'' function<br/>

rawdata <- read.table("http://training-course-material.com/images/1/19/Sales-time-series.txt",h=T) * Equivalent to ARIMA (0,1,1) model with no constant term

'''Question 1''' * Clients[,c(1,2)]

== NPV-1 Programme Portfolio relationships。 == NPV-1 view products represent an organisational perspective on programmes.

* Specifically, the scores on Quiz 1 are more densely packed and those on Quiz 2 are more spread out. * The differences among students were much greater on Quiz 2 than on Quiz 1.

== Exercises 1 ==

...with predefined functions that comes bundled with MediaWiki since version 1.17. {{#if: 1 | yes | no}}

--amazonec2-region eu-west-1 \ aws-machine-1

for elem in [1,2,3,4]: i = i + 1

[1] 2073.214 [1] 14

* The mean and median of the baseball salaries are $1,183,417 and $500,000 respectively. * The standard deviation of the baseball salaries is 1,390,922.

e = a/b # 1 i = 7.0//b # floor div, 1.0

...ded die, the probability of of any given outcome on a single roll would be 1/6 * The data in Table 1 were obtained by rolling a six-sided die 36 times

{{Cat|JBoss AS 5.1}} ...terprise_Web_Server/1.0/pdf/Installation_Guide/JBoss_Enterprise_Web_Server-1.0-Installation_Guide-en-US.pdf

*In the case of coins, heads and tails each have the same probability of 1/2. | 1

* "Gaussian curve" (μ = 0, σ = 1) =NORMDIST(1,0,1,FALSE) = 0.2419707245

*In the case of coins, heads and tails each have the same probability of 1/2. | 1

...utcomes, the probability of any given one of them occurring is taken to be 1/N. * The probability of heads is taken to be 1/2, as is the probability of tails

[1] "2012-04-15" [1] "2012-04-15 03:20:45 BST"

* The scores on Quiz 1 are more '''densely packed''' and those on Quiz 2 are more '''spread out''' ...'''differences''' among students were much greater on Quiz 2 than on Quiz 1

=JBPM 6 - 1.0 - Workbench Overview= == Lab 1.1.1 Executing Process in Kie ==

= Day 1 = == Day 1 Agenda ⌘==

+Always between 0 and 1 (inclusive). ...d scores when there are two or more predictors. It is always between 0 and 1.

* The mean and median of the baseball salaries are $1,183,417 and $500,000 respectively * The standard deviation of the baseball salaries is 1,390,922

...utcomes, the probability of any given one of them occurring is taken to be 1/N. ...e will land up or down. Therefore, the probability of heads is taken to be 1/2, as is the probability of tails.

1. You flip a fair coin 10 times. What is the probability of getting 8 or mor 1.600 2.163 4.000 3.488 4.454 5.100

== NTV-1, Technical Standards Profile。 == * The Technical Standards Profile (NTV-1) provides a list of standards guiding and constraining the implementation o

# Estimate the variance from a sample of 1 if the population mean is known ...of the variance (5-6)2 = 1. We could then average our two estimates (4 and 1) to obtain an estimate of 2.5. Since this estimate is based on two independ

:<math> X_t = c + \sum_{i=1}^p \varphi_i X_{t-i}+ \varepsilon_t \,</math> rawdata <- read.table("http://training-course-material.com/images/1/19/Sales-time-series.txt",h=T)

* Gaussian curve is a special case of a Normal Distribution (μ = 0, σ = 1) =NORMDIST(1,0,1,FALSE) = 0.2419707245

UGPA' = b₁ x HSGPA + b₂ x SAT + A b₁, b₂ are '''regression coefficients''' or '''regression wei

1 BUSH 5000 1 CARNEGIE ANALYST 3000

:1. the sum of squares predicted (SSY') ::*In other words, it is the sum of the y'2 column and is equal to 1.806

'''1. Exercise''' | 1 || 9

* The probability that a one will come up is 1/6 P(1 or 6) = 2/6 = 1/3

'''1. Exercise''' Population 1 mean = 36

* The sum of all probabilities is always 1.0 | 1

* Since there are six possible outcomes, the probability is 1/6. * So the probability of throwing either a one or six is 1/3.

DAY 1 -- HTML & CSS 1. "css_part" folder

* $minKey <= '''chunk1''' < split point 1 <= '''chunk2''' < $maxKey > db.visitors.createIndex({"visitor" : 1})

print s[-1] # last character print s[1:6] # 'anipu'

.....: print query[1] ...r.find_elements_by_xpath("//tr[@class='briefCitRow']//td[3]/table/tbody/tr[1]/td/a")

n1 is the number of times Outcome 1 occurs, p1 is the probability of Outcome 1

1. Create a file structure 1 file changed, 1 insertion(+)

* 1/1000 of drivers are driving drunk | Test Positive || 1 || 0.05

The standard error of the estimate for a population is sqrt[(1-rho2)*SSY/N] sqrt[(1-.52)*50/100] equals .61

daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin

wynik = 1 / 2 * (a + b) * h For a = 1 To 10

s <- read.table("http://training-course-material.com/images/1/19/Sales-time-series.txt",h=T) sts <- ts(s$Price,start=2002,deltat=1/12)

power = 1 - β * The scale of satisfaction is from 1 to 10

;1. The sum of squares predicted (SSY') or Explained Sum of Squares (ESS) ::<math> \sum_{i = 1}^n (Y' - {M'})^2 </math>

σ2 = Nπ(1-π)= (10)(0.5)(0.5) = 2 σ = 1.5811

{{Cat|Estimation|1}} ...of being biased, is fairly accurate. Its measurements are never more than 1.02 pounds from your actual weight.

1. Create a ruleflow where first discount 10% off is calculated into ''discou 1. 新建一个ruleflow，实现第一个10%折扣计入 ''discount'' field�

| 1 ...numbers 1, 10, and 100, the product of all the numbers is: 1 x 10 x 100 = 1,000

** high-self-esteem subjects (esteem = 1) ** succeeded (outcome = 1)

rule "Rule 1" rule "Rule 1"

...rived - ''if Person 1 is a brother of Person 2 therefore Parents of Person 1 are parents of Person 2''

* Agnular 1 vs Angular 2 ** Upgrading from 1

* answer 1

{{Cat|Testing Means| 1}} * The sample mean differed from the hypothesized population mean by 1

=== Using Clipboard 1 ⌘===

//from row number: 1 rule "Row 1 Progressive Discount Table"

(Intercept) 1.63968 0.45150 0.00191 F-statistic: 6.142 on 1 and 18 DF, p-value: 0.02334

* Table 1 shows that this marginal mean is equal to the average of 5.65 and 6.15 whic | Weight || 1 || 10.4673 || 10.4673 || 6.214 || 0.0136

### 1 word_and_tag[1]

[[File:Figure10-1-example-of-process.png|500px]] [[File:FIgure7-1-example-of-a-private-business-process.png|500px]]

;title: BPMN v1.1 - Element Attributes ; StartQuantity 1 : Integer

curl -v -H 'ACCEPT: application/json' 'http://krisv:krisv@10.10.1.16:8080/businesst/query/task' curl_setopt($ch, CURLOPT_RETURNTRANSFER,1);

* Step 1. Using Drools as a library

...elationship between nominal variables for significance. For example, Table 1 shows the data from the Mediterranean Diet and Health case study. Table 1. Frequencies for Diet and Health Study (Outcome).

[[File:Web Services 1.png|400px]] == Web Services History 1 ⌘==

=== Method #1: Filesystem Snapshot ===

** the default mode within MySQL 5.1.12 and later == How Replication Works (part 1)? ⌘==

* OMG Specification (version 1.2 published in January 2019) <small>Decision Model and Notation Beta 1, Figure 1: Aspects of modeling</small>

...le difference between the female mean of 5.35 and the male mean of 3.88 is 1.47 Small-to-moderate violations of assumptions 1 and 2 do not make much difference (simulation in the next section)

licznik = licznik + 1

> db.people.findOne({}, {"Name" : 1, "Nationality" : 1}) > db.people.findOne({}, {"Name" : 1, "Nationality" : 1, "_id" : 0})

1 10 7839 BUSH PRESIDENT NA 17/11/1981 5000 NA ACCOUNTING NEW YO 1 BUSH ACCOUNTING

== NCV-1 Capability vision。 == * The data in an NCV-1 can include:

:* Connection 1 to host 1, connection 2 to host 2, connection 3 to host 1 etc etc ...ound-robin load balancer setup with backends at 127.0.0.1:8001 and 127.0.0.1:8002

...in times for each pair of conditions for each subject is calculated. Table 1 shows these scores for 5 of the 42 subjects. | -1

[1] 0.01063538 0.5834277 1.0000000

| 2 || 1 || 4 || 2 || 8 # The scenarios has been recorded using JMeter v. 2.5.1

1. List employees whose Daily salary is more than 100. #* make sure there is at least 1 row with not active spy

rule "Exercise 1" ==Exercise 1==

=== Common errors (1) ⌘=== large body: 13106010 bytes, client: 127.0.0.1, server: , request:

(Intercept) 0.5397848 0.3177784 1.699 0.0924 . Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

;title: BPMN 2.0 BPMN v1.1 - Loops ;LoopMaximum (0-1) : Integer

Figure 1 shows that the larger the sample size, the higher the power. Since sample s Figure 1. The relationship between sample size and power for H₀: μ = 75,

# <?xml version="1.0" encoding="utf-8"?> [[File:WSDL 1.png|600px]]

===Error Events Example 1⌘=== [[File:FIgure7-1-example-of-a-private-business-process.png|500px]]

=Example 1。= As in Example 1, the shaded area between 80 and 120 contains 68% of the distribution.

...from 66.48 to 113.52. These limits were computed by adding and subtracting 1.96 standard deviations to/from the mean of 90 as follows: 90 - (1.96)(12) = 66.48

* The four conditions are labeled as shown in Table 1. Table 2 shows the data for five subjects. | 1

{ You have 12 numbers. The mean is 3, and the variance is 1. You multiply each number by 4. What is the new variance? 1*(4²) is 16

* Step 1. Check if Firefox is installed ==Step 1: Is Firefox Installed?⌘==

| 1 | 700 | 1200 | 1 7839 BUSH PRESIDENT NA 1981-11-17 5000 NA 10

** Repository 1 （physical storage） *** Project 1（build）

1

### 1 sum(1 for n in wn.all_synsets('n'))

IDEA: Printed handout version of this page (1-3 pages, checklist format? Space for short notes?) ==Day 1==

{{Cat|Power| 1}} power = 1 - β.

>>> a = 1

x = 1; assert (x > 1);

* Therefore, Chi Square with one degree of freedom, written as χ²(1), is simply the distribution of a single normal deviate squared - A Chi Square distribution with 1 df

===6.1 Specification Simplification=== ...y. In particular, the following major changes have been made since UML 2.4.1:

pear config-set auto_discover 1 pear config-set auto_discover 1

bindIp: 127.0.0.1 cacheSizeGB: 1

== Example 1。== * The probability of correctly rejecting a false null hypothesis '''equals 1- β and is called [[:Category:Power|Power]]'''

=== 1.1. Jakie informacje chcemy przechowywać? ⌘=== === 1.2. Jakie tabele powinna zawierać baza? ⌘===

* The independent variable is "Condition" and has two levels (Design 1 and Design 2). ...ere used for the '''two levels''' of the independent variable: the "Design 1" or the "Design 2" '''condition'''.

...ke it operative, it is common to use Modaf Metamodel instead of NAF (as v3.1 does anyway) == NSOV-1 Service taxonomy。 ==

### 1 # 1. Write the function that computes lexical diversity:

| 1 * Likewise, the sum of the absolute deviations from 5 equals 3 + 2 + 1 + 4 + 11 = 21.

===Signal Event Example 1⌘=== ===Error Events Example 1⌘===

== Example 1。== * The probability of correctly rejecting a false null hypothesis '''equals 1- β and is called [[:Category:Power|Power]]'''

Const cs As String = "Provider=OraOLEDB.Oracle.1;Password=asdf;Persist Security Info=False;User ID=SYSTEM;Data k = k + 1

Min. : 9.00 Min. :1.300 -1.04103 -0.50375 0.02616 0.35529 0.99023

1. First, let's create a new route for all our API requests. 1. First, let's build our Angular application by running the Angular-CLI buil

=Example 1= As in Example 1, 68% of the distribution is within one standard deviation of the mean.

There are 5 levels of headings, although level 1 shoudn't be used within a page. <nowiki>line 1</nowiki>

3! = 3 x 2 x 1 = 6 4! = 4 x 3 x 2 x 1 = 24

A common rule of thumb is that an observation with a value of Cook's D over 1.0 has too much influence. ...predictor variable so that it has a mean of 0 and a standard deviation of 1.

git tag v1.1.0 1b2e1d63n git tag -a stable-1 1b2e1d63ff

npm i jquery@1.9.1 == Redux - core concept 1 ⌘==

...strate the concept of sampling distributions with a simple example. Figure 1 shows three pool balls, each with a number on it. Two of the balls are sele Figure 1. The pool balls.

-1. KYDB - Know Your Database 1. Do one part at a time, step by step

=== 1. Compute the means and variances of each group === | False-Felt || 0.46 || 1.65 || 0.649

...2. If P(D') represents the probability that Event D is false, then P(D') = 1 - P(D) = 0.98. ...ndicates that the person doesn't have the disease when he/she really does. 1 - .98 equals to .02

== NCV-1, Capability Vision。 == ...ture which is more general than the scenario-based scope defined in an NOV-1

== NAV-1 Overview and summary information。 == The data in an NAV-1 can include:

* Added MySQL JDBC driver: http://dev.mysql.com/downloads/connector/j/5.1.html * Note the -1, which when combined with a ForEach Logic Controller processes all rows

;1. Create a Group

* allows a user no more than 1 request per second on average, with bursts up to 5 limit_conn connections 1;

| 1.00 | 1.00

* Therefore, Chi Square with one degree of freedom, written as χ²(1), is simply the distribution of a single normal deviate squared - A Chi Square distribution with 1 df

== NSV-1 System interface description。 == ...tor (i.e. a line with possible amplifying information). The data in an NSV-1 can include:

1. Family example Ex3.1. Rewrite previous solution: pair ?container and ?what in select clause.

===Error Events Example 1⌘=== * Zadanie 1. Logowanie

;title: NAF - Part 3.1 - NATO All View == NAV-1, Overview and Summary Information。 ==

:nth-child -- p:nth-child(1) -- what happens?

| 1 | 1

...for each y value. Then add these values together. (-2)(0) + (0)(-1) + (2)(1) is 2

def calc_price(fruit,n=1):

=== Exercise 1 ⌘=== ; settings[breadcrumbs] = 1

3! = 3 x 2 x 1 = 6 4! = 4 x 3 x 2 x 1 = 24

=== Parallel Gateway Example 1⌘=== === Inclusive Gateway Example 1⌘===

UGPA' = b₁HSGPA + b₂SAT + A HSGPA' = -1.314 + 0.0036 x SAT

H0: μ1 = μ2 = ... μk | 1

The binomial distribution for N = 16 and π = 0.50 is shown in Figure 1. The probability of being correct on 11 or more trials is 0.105 and the pro Figure 1. The binomial distribution for N = 16 and π = 0.50.

=== Exercise 1 ⌘=== <!-- Example of solution to Ex 1

=== Parallel Gateway Example 1⌘=== * Exercise 1.

| 1% | Defects will be reduced from 3 in every 1,000 to 1 in every 1,000 by June.

* SOV-1 Service Taxonomy (SoaML: Category)

HTTP/1.1 302 Moved Temporarily Server: nginx/1.4.1

* usually there are 1 or a few optimal solutions * There is always at least 1 optimal solution, even in the case that there are no feasible solutions and

= JBPM 6 - 1.6 - Triggering Process via REST 通过REST触发流程 = * http://docs.jboss.org/jbpm/v6.1/userguide/jBPMRemoteAPI.html

{{Cat|NobleProg BPMN Certification Level 1|01.1}} AKA: 1-out-of-M join.

upper limit: 0.425 + (3.182)(0.305) = 1.40 { 1.47 }

> db0.adminCommand({"shutdown" : 1}) .../data/np_rep/rep0 --logpath /data/np_rep/rep0.log --fork --bind_ip 127.0.0.1 --rest --httpinterface --logappend

{A wallet contains 3 $100 bills and 5 $1 bills. You randomly choose 4 bills. What is the probability that you will c

[[File:1. Emirates_logo2.png|100px]]

| 1 || Female || 8 {There is an A x B interaction if the effect of A is different at level 1 of B than it is at level 2 of B.

== 1 SOURCES AND FURTHER READING ⌘==

...low-fat no-exercise condition, the means are weighted by factors of 4 and 1 as shown below where M_w is the weighted mean. | M=-1.25

a = numpy.array( [1,2,3,4,5,6] )

{{Cat|NobleProg BPMN Certification Level 1|02.2}}

power = 1 - β. The binomial distribution for N = 16 and π = 0.50 is shown in Figure 1. The probability of being correct on 11 or more trials is 0.105 and the pro

** number of values: 1 * Allow override node pages (node/1)

| exactly one || '''1''' | zero or one || '''0..1'''

* key/value pairs are ordered {"x" : 1, "y" : 1} != {"y" : 1, "x" : 1} ** number (by default 64-bit floating point numbers) {"x" : 1.4142}

...n average of k variances each with n-1 df. Therefore the df for MSE is k(n-1) = N-k where N is the total number of scores, n is the number in each group df_numerator = k-1

FORD 1 THATCHER 1

| 1.00 | 1.00

业界资讯：GitHub searches 20TB of data using Elasticsearch, including 1.3 billion files and 130 billion lines of code. （1）Open Source（开源）

SAL_labels <- round(emp$SAL/sum(emp$SAL) * 100, 1) 1. Create a Barchart for the sales by country.

| -1 | 1

<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> === Responsive utilities 1 ⌘===

== NSOV-1, Service Taxonomy。 == === NSOV-1, Service Taxonomy。 ===

### 1 # - PER: 1 (I, we) or 2 (you) or 3 (he, she, it, they)

[then]Set discount to {discount} = sc.setTotalPrice( $totalPrice * (1-{discount}) ); update(sc); Set discount to 0.1

*2007 Feb 14 - GIT 1.5.0 is released (more humane) 1. Create a file structure

* There can be more than 1 KPI per CSF # Assign at least 1 Measure for each Factor (KPI)

=== Parallel Gateway Example 1⌘=== * Zadanie 1: Lotnisko

<a href="index.html">Menu item 1</a> <p>Element 1. I aim to create simple yet engaging Web sites that

== XLS Decision Table example 1⌘==

COPY ["file 1", "dir 1", "/dest/dir/"] LABEL version="1.0" description="Docker Training" maintainer="Kamil Baran"

| 1.00 | 1.00

1. "SELECT" clause, by itself only WHERE col4 IN (1, 2, 5) AND col5 < 700

;Example 1 ;Example 1

Power = 1 - β

== NOV-1 High level operational concept description == An NOV-1 is typically just a graphic. The data to be included in an NOV-1 can be any business objects of interest, including:

HTTP/1.1 302 Moved Temporarily proxy_cache_path /var/spool/nginx keys_zone=CACHE:100m levels=1:2 inactive=6h max_size=1g;

{{Collapse|Misconception 1: The probability value is the probability that the null hypothesis is false

...ate && sudo apt-get install -y kubeadm=1.21.5-00 kubectl=1.21.5-00 kubelet=1.21.5-00 kubectl apply -f https://github.com/weaveworks/weave/releases/download/v2.8.1/weave-daemonset-k8s.yaml

{{Cat|JBoss AS 5.1}} * Subscribe to Supplementary Server channel + yum install java-1.6.0-sun-devel

1. Server and repos preparations: svn log --xml --quiet | grep author | sort -u | perl -pe 's/.*>(.*?)<.*/$1 = /' > users1.txt

* NAF 3.1 uses MoDAF 1.2.003 metamodel ...e the following diagrams of follow the link below to learn about version 3.1