Project managers organize different resources like people, Cheat Sheet of Project Management

Download Project managers organize different resources like people and more Cheat Sheet Project Management in PDF only on Docsity! Using analytical techniques ‘ obeetee. °o 82 oteee te te sderen go gd ice PC a sate este ofpgeere pe nace gee tse ce es e o seen enene thaletegeetee ccccastentes otthsentteneccste setts es scomeenertagets on pants te 7S cons*eoesestyece ees TREND ANALYSIS  Trend analysis as a design research methodology involves collecting data about users as well as from users.   This data is then analyzed to determine a trend and is then analyzed further to determine its development over time.  Trend analysis is the practice that gives us the ability to look at data over time for a long-running survey. Method Geographic Temporal TYPES OF TREND ANALYSIS Purpose To analyze the trend within or across user groups defined by their geographic location. To analyze the trend within or across user groups defined by specific time period(s) or change over time. Advantages Easy and reliable. Helpful in figuring our commonalities and differences between user groups belonging to the same as well as different geographies. Helpful in figuring relationships between user groups from different generations. Helpful in Disadvantages The analysis is limited to geography. May be influenced by factors such as culture, etc. specific to the user groups of the geography. Historical data may not be an accurate representation of trends. The trend may not be replicable. Method Intuitive Purpose To analyze the trend within or across user groups based on some logical explanation, behavioral patterns or other elements perceived by a futurist. Advantages Helpful when making predictions not backed by large amounts of Statistical data. Disadvantages ® Over reliance on knowledge and logic of futurists/researchers. ® Prone to researcher bias. e Most difficult form of trend analysis. e Not exacting Advantages of Trend Analysis  1. Large sample sizes  The availability of data and online tools available to handle large amounts of data allow for sampling of data quickly and applying the results to a variety of situations.  2. Verifiable  The results of trend analysis are easily verifiable.  3. Accurate  In case of statistical data, the analysis is very close to accurate. The use of numbers makes the analysis more exacting.  4. Replicable  A trend analysis can be replicated, verified, altered and adjusted when necessary. Sources and access to, data  In research, data can be obtained from a variety of sources, including:  Open and public data: This includes data that is publicly available, such as government statistics, open-access databases, and data released by non-profit organizations.  Administrative data: This refers to data collected by government agencies or other organizations for administrative purposes, such as demographic data, health records, and educational records.  Sensitive data: This includes personal and confidential information, such as financial records, medical records, and criminal records, that requires special protection due to ethical and legal considerations.  Research data: This is data collected specifically for a research project, such as survey responses, laboratory measurements, and observational data.  Access to these different types of data is often governed by laws, regulations, and policies.  For example, access to sensitive data may be restricted due to privacy and security concerns, while open and public data is generally more accessible.  Researchers must take into consideration ethical and legal requirements when accessing and using data in their research. The principles of data governance  In a research context, these principles of data governance can play a crucial role in ensuring the quality and integrity of the data used in a study.  By recognizing the value of data, researchers can prioritize its proper collection, management, and preservation.  Reusable data can serve as a valuable resource for future research, while managing data according to its value can help allocate resources and ensure that important data is preserved.  Making sure that data is fit for its intended purpose is essential for the validity of the research findings. By adhering to these principles, researchers can improve the reliability and reproducibility of their work. Reliability and validity of the result  Reliability and validity are important characteristics of research.   Reliability refers to the consistency and stability of research results  When a study is reliable, similar results should be obtained if the study were repeated with a similar sample.  Validity, on the other hand, refers to the accuracy and truthfulness of research results. A study is considered valid if it measures what it aims to measure and if the results accurately reflect the true state of the world.  Both reliability and validity are important for ensuring that research results are trustworthy and useful.   Researchers should strive to design and conduct studies that are both reliable and valid, and should also be transparent about their methods and results,   so that their work can be independently assessed and verified. Validity and reliability of Secondary Data  Validity refers to the accuracy and truthfulness of the data and information being used  Secondary data may not always be completely valid, as the data may have been collected for a different purpose or may be outdated.   To ensure validity, researchers should critically evaluate the sources of the data and verify their accuracy.