ZachNewmanReeshMethblog2017-2018

Part VIII Chapter 25: Covers the most common kinds of quantitative data statistics and the reasons behind them. 1. Chance in studies can act as its down fall as it will more often then not result in inaccurate information.  "Because we are rarely able to study an entire population, we are almost always dealing with samples drawn from that population" (Grinnell 519). 2. The Dependent and Independent tests are the two kinds that can determine difference. The main way to tell them apart is how the groups being tested relate to one another. 3. Statistical measurement is critical in analysis and selecting the right measuring tools is impotent for that. The goal in an measuring is to eliminate as much error as possible before and during the test. Chapter 26: is on analyzing data through a theoretical approach of the data. 1. Credibility in a study is very important for it to be considered a good one. If a study is n...

Chapter 18 Thesis: This chapter covers the six basic methods and tactics of data recording and collection in the form of structured observation. 1. Structured observation, observation made with trained observers under very specific conditions to the specific research. "In addition, it is the most obstructive data collection method that can be used in social work research situations" (Grinnell 374). 2. "The method chosen must be consistent with the characteristics of the target problem being observed" (Grinnell 374). We have to do this to be sure we get good data from our tests and observations in our research.  3. The selection of the observer is just as impotent as the method to getting good data in your research. "Observer reliability it analogous to the test-retest and alternate-forms methods of establishing reliability of measuring instruments discussed in Chapter 13" (Grinnell 384). Reliability is key to having a useful...

Chapter 15 Thesis:  Sampling is incredibly   impotent  for research and chapter 15 is on the basics of this process.   Observations: 1. "Sampling is very common in research studies, but sometimes it isn't necessary" (Grinnell 292). It is important to know when to use sampling in order to get the best effect from it and not waste any resources when it is not necessary. Just because something is common that does not mean it is always the right thing to do. 2. There are two main types of sampling methods and distinguishing between them is very important as they have very different uses. "The most important distinction that needs to be made about samples is whether they are based on a probability sampling method or a nonprobability sampling method" (Grinnell 297). 3. When taking a sample the size of it is very impotent to determining the validity of the research. "Unfortunately, researchers often cannot afford to sample a very large number of cases"...

Part 5 Chapter 12 Thesis: This chapter is about the impotence of measurement and the necessity to verify the tools that that give them to you as to make sure you get the best data. 1. Without taking accurate measurements and cataloging the information we discover there is no science just messing around "Measurement helps take some of the guesswork out of scientific observation" (Grinnell 237). Anyone can think anything but without evidence it is very difficult to convince people to see the world your way. 2. The information we collect can't only inserting but also relevant to the world or the community. "Moreover, the data gathered to measure the variables must be directly relevant and meaningful to these variables" (Grinnell 239). 3. Their is no such thing as one hundred present certainty because if there was we would never fight about anything as their would always be a correct answer. This must be kept in mind when using research equipment. "Conseq...