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Exam Number : MOPF
Exam Name : M_o_P (Management of Portfolio Foundation)
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EXAM CODE: MOPF
EXAM NAME: M_o_P (Management of Portfolio Foundation)

Portfolio management helps organizations make decisions about implementing the right changes to their business as usual (BAU) activity via projects and programmes. The Management of Portfolios (MoP®) guidance provides senior executives and practitioners responsible for planning and implementing change, with a set of principles, techniques and practices to introduce or re-energize portfolio management.

- Senior management engagement supports effective portfolio management.
- Senior managers should support portfolio management.
- Approaches and techniques to align programmes and projects with organizational strategy.
- Techniques that facilitate strategic alignment even where strategic measures are not clearly defined.
- The services it provides.
- How it differs from a programme or project office.
- The elements of an energized change culture.
- The energy states.
- Sources of organizational energy.
- Understand
- Categorize
- Prioritize
- Balance
- Plan
- Three point estimating and reference class forecasting.
- Driver-based strategic contribution analysis.
- Multi-criteria analysis.
- Decision conferencing.
- Clear line of sight planning.
- Understanding the current portfolio.
- Splitting the portfolio into organizationally appropriate categories or segments.
- Using appropriate approaches to prioritize the portfolio.
- Considering what factors need to be taken into account in balancing the portfolio.
- Completing a portfolio strategy and delivery plan.
- Whether the approaches adopted are appropriate, with reasons, in a given scenario when:
- Understanding the current portfolio.
- Categorizing the portfolio.
- Prioritizing the portfolio.
- Balancing the portfolio.
- Completing a portfolio strategy and delivery plan.
- Management control
- Benefits management
- Financial management
- Risk management
- Stakeholder engagement
- Organizational governance
- Resource management
- Management by exception
- One version of the truth
- Staged release of funding
- Clear line of sight reporting
- Champion-challenger model
- Management control
- Portfolio-level benefits management
- Portfolio-level financial management
- Portfolio-level risk management
- Portfolio-level stakeholder engagement
- Portfolio-level resource management
- Management control
- Portfolio-level benefits management
- Portfolio-level financial management
- Portfolio-level risk management
- Portfolio-level stakeholder engagement
- Portfolio-level resource management
- The purposes of the main portfolio management roles identified in MoP:
- Portfolio Direction Group/Investment Committee
- Portfolio Progress Group/Change Delivery Committee
- Business Change Director/Portfolio Director
- Portfolio Manager
- Portfolio Benefits Manager
- The purposes of the main portfolio management documentation:
- Portfolio Management Framework
- Portfolio Benefits Management Framework
- Portfolio Strategy
- Portfolio Delivery Plan
- Portfolio Benefits Realization Plan
- Portfolio Financial Plan
- Portfolio Resource Schedule
- Portfolio Stakeholder Engagement and Communication Plan
- Portfolio Dashboard Report
- 01 The responsibilities of the main portfolio roles identified in MoP:
- Portfolio Direction Group/Investment Committee
- Portfolio Progress Group/Change Delivery Committee
- Business Change Director/Portfolio Director
- Portfolio Manager
- Portfolio Benefits Manager
- The recommended contents of the main portfolio management documentation:
- Portfolio Management Framework
- Portfolio Benefits Management Framework
- Portfolio Strategy
- Portfolio Delivery Plan
- Portfolio Benefits Realization Plan
- Portfolio Financial Plan
- Portfolio Resource Schedule
- Portfolio Stakeholder Engagement and Communication Plan
- Portfolio Dashboard Report
- Identify appropriate information, using typical contents, for inclusion
- Portfolio Management Framework
- Portfolio Benefits Management Framework
- Portfolio Strategy
- Portfolio Delivery Plan
- Portfolio Benefits Realization Plan
- Portfolio Financial Plan
- Portfolio Resource Schedule
- Portfolio Stakeholder Engagement and Communication Plan
- Portfolio Dashboard Report
- Portfolio Direction Group/Investment Committee
- Portfolio Progress Group/Change Delivery Committee
- Business Change Director/Portfolio Director
- Portfolio Manager
- Portfolio Benefits Manager
- Portfolio Management Framework
- Portfolio Benefits Management Framework
- Portfolio Strategy
- Portfolio Delivery Plan
- Portfolio Benefits Realization Plan
- Portfolio Financial Plan
- Portfolio Resource Schedule
- Portfolio Stakeholder Engagement and Communication Plan
- Portfolio Dashboard Report
- Portfolio Direction Group/Investment Committee
- Portfolio Progress Group/Change Delivery Committee
- Business Change Director/Portfolio Director
- Portfolio Manager
- Portfolio Benefits Manager



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T-test: What it's With numerous formulas and When to make use of Them | Killexams.com Resources

what is a T-verify?

A t-test is an inferential statistic used to check if there's a major change between the capacity of two groups and how they're linked. T-tests are used when the information sets observe a standard distribution and have unknown variances, just like the facts set recorded from flipping a coin a hundred instances.

The t-verify is a check used for speculation trying out in information and makes use of the t-statistic, the t-distribution values, and the levels of freedom to examine statistical magnitude.

Key Takeaways
  • A t-look at various is an inferential statistic used to check if there's a statistically gigantic difference between the skill of two variables.
  • The t-verify is a look at various used for hypothesis checking out in information.
  • Calculating a t-check requires three basic facts values together with the difference between the mean values from every statistics set, the ordinary deviation of each group, and the variety of statistics values.
  • T-checks may also be stylish or impartial.
  • Investopedia / Sabrina Jiang

    knowing the T-test

    A t-examine compares the regular values of two statistics units and determines in the event that they got here from the equal population. within the above examples, a trial of scholars from type A and a pattern of students from category B would not probably have the same suggest and general deviation. in a similar fashion, samples taken from the placebo-fed control group and people taken from the drug prescribed community should still have a a bit diverse imply and usual deviation.

    Mathematically, the t-look at various takes a trial from each of both units and establishes the difficulty commentary. It assumes a null hypothesis that the two capacity are equal.

    using the formulas, values are calculated and compared in opposition t the general values. The assumed null speculation is permitted or rejected as a result. If the null speculation qualifies to be rejected, it suggests that data readings are robust and are probably no longer because of chance.

    The t-verify is just one of many exams used for this aim. Statisticians use extra exams other than the t-look at various to determine more variables and greater trial sizes. For a large trial size, statisticians use a z-examine. other checking out alternatives consist of the chi-square verify and the f-look at various.

    the use of a T-verify

    believe that a drug brand tests a new drugs. Following average technique, the drug is given to 1 neighborhood of patients and a placebo to an additional group called the handle group. The placebo is a substance without a therapeutic cost and serves as a benchmark to measure how the other group, administered the specific drug, responds.

    After the drug trial, the contributors of the placebo-fed control community said an increase in average lifestyles expectancy of three years, whereas the individuals of the neighborhood who're prescribed the new drug said an increase in typical existence expectancy of four years.

    initial observation indicates that the drug is working. youngsters, it is additionally viable that the commentary could be due to possibility. A t-examine can be used to examine if the results are suitable and applicable to the whole population.

    four assumptions are made while the use of a t-look at various. The facts accumulated must comply with a continuous or ordinal scale, such because the rankings for an IQ test, the records is gathered from a randomly selected component of the full population, the records will effect in a standard distribution of a bell-shaped curve, and equal or homogenous variance exists when the normal adaptations are equal.

    T-test method

    Calculating a t-verify requires three fundamental statistics values. They include the change between the suggest values from every facts set, or the mean difference, the ordinary deviation of every community, and the variety of information values of every neighborhood.

    This evaluation helps to verify the effect of probability on the change, and even if the change is outside that chance latitude. The t-test questions no matter if the difference between the corporations represents a real difference in the study or in basic terms a random change.

    The t-examine produces two values as its output: t-value and levels of freedom. The t-value, or t-rating, is a ratio of the difference between the suggest of the two trial sets and the adaptation that exists within the trial sets.

    The numerator price is the change between the imply of both pattern sets. The denominator is the version that exists inside the trial sets and is a size of the dispersion or variability.

    This calculated t-price is then compared in opposition t a price obtained from a vital value desk known as the T-distribution table. higher values of the t-score point out that a big change exists between both pattern sets. The smaller the t-price, the more similarity exists between the two trial sets.

    T-score

    a big t-score, or t-cost, shows that the organizations are diverse while a small t-ranking suggests that the businesses are similar.

    levels of freedom refer to the values in a study that has the liberty to vary and are primary for assessing the value and the validity of the null speculation. Computation of these values continually relies on the variety of records information accessible in the pattern set.

    Paired trial T-examine

    The correlated t-look at various, or paired t-check, is a dependent class of test and is carried out when the samples include matched pairs of identical contraptions, or when there are cases of repeated measures. for instance, there can be instances the place the identical patients are again and again validated before and after receiving a selected remedy. each and every patient is getting used as a handle pattern towards themselves.

    This components additionally applies to cases where the samples are connected or have matching traits, like a comparative analysis involving babies, folks, or siblings.

    The components for computing the t-price and degrees of freedom for a paired t-check is:

    T = imply 1 − imply 2 s ( diff ) ( n ) where: suggest 1  and  imply 2 = The normal values of each of the sample sets s ( diff ) = The commonplace deviation of the variations of the paired records values n = The sample measurement (the quantity of paired differences) n − 1 = The degrees of freedom \startaligned&T=\frac\textitsuggest1 - \textitimply2\fracs(\textdiff)\sqrt(n)\\&\textbfwhere:\\&\textitimply1\textual content and \textitsuggest2=\textThe normal values of each of the pattern units\\&s(\textual contentdiff)=\textThe typical deviation of the adjustments of the paired information values\\&n=\textThe trial measurement (the variety of paired modifications)\\&n-1=\textThe levels of freedom\endaligned ​T=(n)​s(diff)​mean1−mean2​the place:mean1 and mean2=The normal values of every of the sample setss(diff)=The ordinary deviation of the transformations of the paired statistics valuesn=The pattern dimension (the number of paired changes)n−1=The levels of freedom​

    Equal Variance or Pooled T-examine

    The equal variance t-verify is an impartial t-check and is used when the number of samples in every neighborhood is the same, or the variance of the two records units is equivalent.

    The components used for calculating t-price and degrees of freedom for equal variance t-verify is:

    T-cost = m e a n 1 − m e a n 2 ( n 1 − 1 ) × v a r 1 2 + ( n 2 − 1 ) × v a r 2 2 n 1 + n 2 − 2 × 1 n 1 + 1 n 2 where: m e a n 1  and  m e a n 2 = common values of every of the sample units v a r 1  and  v a r 2 = Variance of each of the pattern sets n 1  and  n 2 = quantity of statistics in each pattern set \beginaligned&\textT-value = \frac mean1 - mean2 \frac (n1 - 1) \instances var1^2 + (n2 - 1) \times var2^2 n1 +n2 - 2\times \sqrt \frac1n1 + \frac1n2 \\&\textbfwhere:\\&mean1 \textual content and mean2 = \textordinary values of each \\&\textof the pattern sets\\&var1 \textual content and var2 = \textVariance of each of the trial sets\\&n1 \text and n2 = \textual contentnumber of records in every pattern set \conclusionaligned ​T-value=n1+n2−2(n1−1)×var12+(n2−1)×var22​×n11​+n21​​mean1−mean2​where:mean1 and mean2=standard values of eachof the pattern setsvar1 and var2=Variance of each of the sample setsn1 and n2=number of data in each and every pattern set​

    and,

    degrees of Freedom = n 1 + n 2 − 2 the place: n 1  and  n 2 = number of statistics in every sample set \beginaligned &\textlevels of Freedom = n1 + n2 - 2 \\ &\textbfthe place:\\ &n1 \text and n2 = \textual contentnumber of statistics in every trial set \\ \conclusionaligned ​levels of Freedom=n1+n2−2where:n1 and n2=number of records in each and every sample set​

    Unequal Variance T-verify

    The unequal variance t-verify is an unbiased t-look at various and is used when the variety of samples in each and every community is distinct, and the variance of both statistics sets is also diverse. This verify is also known as Welch's t-examine.

    The system used for calculating t-value and levels of freedom for an unequal variance t-test is:

    T-value = m e a n 1 − m e a n 2 ( v a r 1 n 1 + v a r 2 n 2 ) the place: m e a n 1  and  m e a n 2 = common values of each and every of the sample sets v a r 1  and  v a r 2 = Variance of every of the sample sets n 1  and  n 2 = quantity of records in each and every pattern set \beginaligned&\textT-cost=\fracmean1-mean2\sqrt\bigg(\fracvar1n1+\fracvar2n2\bigg)\\&\textbfwhere:\\&mean1 \text and mean2 = \textual contentcommon values of each \\&\textof the pattern units \\&var1 \textual content and var2 = \textual contentVariance of each of the pattern sets \\&n1 \textual content and n2 = \textnumber of statistics in each and every pattern set \conclusionaligned ​T-price=(n1var1​+n2var2​)​mean1−mean2​where:mean1 and mean2=general values of eachof the pattern setsvar1 and var2=Variance of each and every of the pattern setsn1 and n2=number of facts in every pattern set​

    and,

    degrees of Freedom = ( v a r 1 2 n 1 + v a r 2 2 n 2 ) 2 ( v a r 1 2 n 1 ) 2 n 1 − 1 + ( v a r 2 2 n 2 ) 2 n 2 − 1 the place: v a r 1  and  v a r 2 = Variance of each and every of the sample sets n 1  and  n 2 = number of records in each and every sample set \beginaligned &\textlevels of Freedom = \frac \left ( \frac var1^2 n1 + \frac var2^2 n2 \right )^2 \frac \left ( \frac var1^2 n1 \right )^2 n1 - 1 + \frac \left ( \frac var2^2 n2 \appropriate )^2 n2 - 1 \\ &\textbfwhere:\\ &var1 \text and var2 = \textual contentVariance of each and every of the pattern sets \\ &n1 \text and n2 = \textnumber of statistics in each and every pattern set \\ \endaligned ​degrees of Freedom=n1−1(n1var12​)2​+n2−1(n2var22​)2​(n1var12​+n2var22​)2​where:var1 and var2=Variance of each and every of the sample setsn1 and n2=number of information in each and every pattern set​

    Which T-examine to make use of?

    the following flowchart may also be used to assess which t-check to use in accordance with the characteristics of the trial sets. the key items to consider encompass the similarity of the trial statistics, the variety of data records in every pattern set, and the variance of every pattern set.

    image by way of Julie Bang © Investopedia 2019

    illustration of an Unequal Variance T-check

    anticipate that the diagonal dimension of paintings bought in an art gallery is taken. One community of samples contains 10 paintings, whereas the other comprises 20 art work. The data units, with the corresponding suggest and variance values, are as follows:

      Set 1 Set 2   19.7 28.three   20.4 26.7   19.6 20.1   17.eight 23.3   18.525.2   18.922.1   18.3 17.7   18.927.6   19.520.6   21.ninety five 13.7     23.2     17.5     20.6     18     23.9     21.6     24.three     20.four     23.9     13.three mean 19.4 21.6 Variance 1.four 17.1

    even though the imply of Set 2 is bigger than that of Set 1, they can not conclude that the inhabitants akin to Set 2 has a more robust suggest than the population comparable to Set 1.

    Is the difference from 19.4 to 21.6 because of opportunity by myself, or do variations exist within the universal populations of the entire art work acquired in the artwork gallery? They set up the difficulty by means of assuming the null hypothesis that the mean is a similar between both pattern units and habits a t-check to examine if the hypothesis is plausible.

    when you consider that the variety of statistics statistics is diverse (n1 = 10 and n2 = 20) and the variance is also diverse, the t-value and degrees of freedom are computed for the above statistics set using the system mentioned in the Unequal Variance T-look at various part.

    The t-cost is -2.24787. on account that the minus signal can be neglected when comparing both t-values, the computed value is 2.24787.

    The levels of freedom value is 24.38 and is decreased to 24, owing to the method definition requiring rounding down of the cost to the least possible integer cost.

    you can still specify a level of likelihood (alpha level, level of importance, p) as a criterion for acceptance. In most instances, a 5% cost can also be assumed.

    using the degree of freedom price as 24 and a 5% level of value, a look at the t-cost distribution desk gives a price of 2.064. comparing this cost in opposition t the computed cost of 2.247 indicates that the calculated t-value is more suitable than the desk value at a importance level of 5%. hence, it is protected to reject the null hypothesis that there is no change between capability. The inhabitants set has intrinsic variations, and they're not by accident.

    How Is the T-Distribution desk Used?

    The T-Distribution desk is available in one-tail and two-tails formats. the previous is used for assessing instances which have a set price or range with a transparent direction, both high quality or negative. as an instance, what is the likelihood of the output price final under -three, or getting greater than seven when rolling a pair of cube? The latter is used for range-sure evaluation, corresponding to asking if the coordinates fall between -2 and +2.

    what's an impartial T-examine?

    The samples of impartial t-exams are selected impartial of each and every different the place the data sets within the two organizations don’t discuss with the equal values. They can also include a gaggle of 100 randomly unrelated patients split into two organizations of 50 patients each and every. one of the crucial organizations turns into the control group and is run a placebo, whereas the different group receives a prescribed remedy. This constitutes two unbiased trial groups that are unpaired and unrelated to every different.

    What Does a T-examine explain and how Are They Used?

    A t-test is a statistical verify it's used to examine the means of two agencies. it is frequently used in speculation checking out to examine whether a system or treatment has an effect on the inhabitants of activity, or even if two corporations are different from one another.


     



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