UDJ| FINANCE|
Use/Name| Formula| Use/Name| Formula|
Variance (2)(For Poisson, equal to mean)| or n*p*(1-p)| NPV(Costs up front)| | Standard Deviation ()| | Discount Factor| _1_(1+r)n| Exp. Val E(W)of combined linear function| a + bμx + cμxWhere b&c are weights| Annuity Discount Factor| 1-DF or 1-_1_ k ( 1+r)n k| Variance (2)of combined lin funct (X,Y)| b2V(x)+c2V(y)+2bc•Cov(x,y)Where b&c are weights| AnnuityPresent Value| CF X ADF or | Covariance| x y COR(X,Y)| AnnuityFuture Value| |

Correlation (ρ)| | AnnuityPayment| |
Mean| fixi| Growing AnnuityPresent Value| |
Variance Of a Sample (s2)| sqrt to get std dev (s)| PerpetuityPresent Value| CFK| Standard Error(Then to Margin of Error & Confidence Interval)| s/√nwhere s= √x̄(1- x̄)[* (Zɑ/2) for MoE][ ↳ ± x̄ for CI]| Bond Duration| | RequiredSample Size(rework of above)| or | Variance (2)of a portfolio (X,Y)| b2E(x) 2+c2E(y) 2+2bc•Cov(x,y)Where b&c are weights| Confidence IntervalFor a proportion| | SharpeRatio| | Zobs| | Exp. Return of a portfolio| |

Test StatisticZ values Proportions Take this to the table for “P Value”| | βof a portfolio| or | X criticalproportions| Evaluation criteria:| CMLEquation| | | | Cost of Levered Equity| |

| | WACC| |
| | Levered vs. Unlevered Beta| |

μ = x̄ = E(x) Mean| n = number| CF = P = Cashflow or Payment| fi = rel. freq| = Sum of a series| T = time|
xi = middle point| ρ = Correlation| k = r = interest rate| W = combined linear func| = Standard Deviation| g = growth| 2 = Variation| ɑ = E = Margin of Error| rp = Risk of Portfolio| p0 = proportion of hypothesis| β = Beta coeffic. of portfolio| rf = Risk Free Rate|

...Normal(88.532,5.07943)
Normal(97.1033,5.04488)
Normal(107.15,5.15367)
Summary Statistics
Mean
88.532
Std Dev
5.0794269
Std Err Mean
0.2271589
Upper 95% Mean
88.978306
Lower 95% Mean
88.085694
N
500
Sum
44266
Summary Statistics
Mean
97.103333
Std Dev
5.0448811
Std Err Mean
0.2912663
Upper 95% Mean
97.676525
Lower 95% Mean
96.530142
N
300
Sum
29131
Summary Statistics
Mean...

...the written application of operation. It teaches students to think clearly, reason well and strategize effectively. Mental Mathematics is the ability to utilise mathematical skills to solve problems mentally. The marks scored by pupils generate statistics which are used by teachers to analyse a student’s performance and development of theories to explain the differences in performance.
The Standard 3 class is where the transition from junior to senior level occurs where...

...Department of Decision Sciences
Rational Decision Making
Only study guide for
DSC2602
University of South Africa
Pretoria
c 2010 University of South Africa
All rights reserved.
Printed and published by the
University of South Africa,
Muckleneuk, Pretoria.
DSC2602/1/2011
Cover: Eastern Transvaal, Lowveld (1928) J. H. Pierneef
J. H. Pierneef is one of South Africa’s best known artists.
Permission for the use of this work was kindly granted...

...Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times...

...Statistics 1
Business Statistics
LaSaundra H. – Lancaster
BUS 308 Statistics for Managers
Instructor Nicole Rodieck
3/2/2014
Statistics 2
When we hear about business statistics, when think about the decisions that a manager makes to help make his/her business successful. But do we really know what it takes to run a business on a statistical level? While some may think that...

...Scatterplots 4
Pearson’s Correlation 4
Spearman’s Rho 4
Probability 4
Binomial Distribution 4
Assumptions: 5
Subjective Probability 5
Normal Distribution 5
Standard Normal Distribution 5
Sampling Distribution 5
Standard Error of Statistic 5
Central Limit Theorem 5
Area under the Sampling Distribution of the Mean 6
Sampling Distribution, Difference between Independent means 6
Sampling Distribution of a Linear Combination of Means 6
Sampling...

...Organization of Terms
Experimental Design
Descriptive
Inferential
Population
Parameter
Sample
Random
Bias
Statistic
Types of
Variables
Graphs
Measurement scales
Nominal
Ordinal
Interval
Ratio
Qualitative
Quantitative
Independent
Dependent
Bar Graph
Histogram
Box plot
Scatterplot
Measures of
Center
Spread
Shape
Mean
Median
Mode
Range
Variance
Standard deviation
Skewness
Kurtosis
Tests of
Association
Inference
Correlation...

1764 Words |
6 Pages

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