Research Methods and Statistics: A Critical Thinking Approach DOWNLOAD PDF .. The Scientific (Critical Thinking) Approach and Psychology Systematic. (Free and download) Research Methods and Statistics: A Critical Thinking Approach. Research Methods audiobook | *ebooks | Download PDF | ePub | DOC. Book details Author: Sherri Jackson Pages: pages Publisher: Wadsworth Publishing Language: English ISBN ISBN Description this book Research Methods and Statistics: A Critical Thinking Approach, 5th Edition, successfully.
|Language:||English, Dutch, French|
|Genre:||Business & Career|
|ePub File Size:||15.46 MB|
|PDF File Size:||14.44 MB|
|Distribution:||Free* [*Registration needed]|
Research methods and statistics a critical thinking approach pdf. Book Research Methods and Statistics: A Critical Thinking Approach by Sherri L. Jackson PDF ePUB MOBI Free PDF File. Trove: Find and get Australian resources. Books, images, historic newspapers, maps, archives and more.
It would be nice if it did because then we would not have to worry about being either underweight or overweight. What if I told you that watching violent TV and displaying aggressive behavior were correlated?
What could you conclude based on this correlation? Many people might conclude that watching violent TV causes one to act more aggressively. Based on the evidence given a correlational study , however, we cannot draw this conclusion.
All we can conclude is that those who watch more violent television programs also tend to act more aggressively. It is possible that violent TV causes aggression, but we cannot draw this conclusion based only on correlational data.
The point is that observing a correlation between two variables means only that they are related to each other. Thinking Like a Scientist The correlation between height and weight, or violent TV and aggressive behavior, is a positive relationship: As one variable height increases, we observe an increase in the second variable weight.
Some correlations indicate a negative relationship, meaning that as one variable increases, the other variable systematically decreases. Can you think of an example of a negative relationship between two variables? Consider this: As mountain elevation increases, temperature decreases.
Negative correlations also allow us to predict from one variable to another. If I know the mountain elevation, it will help me predict the approximate temperature.
Besides the correlational method, a second method that allows us to describe and predict is the quasi-experimental method. The quasiexperimental method allows us to compare naturally occurring groups of individuals.
For example, we could examine whether alcohol consumption by students in a fraternity or sorority differs from that of students not in such organizations.
You will see in a moment that this method differs from the experimental method, described later, in that the groups studied occur naturally.
In other words, we do not control whether or not people join a Greek organization. They have chosen their groups on their own, and we are simply looking for differences in this case, in the amount of alcohol typically consumed between these naturally occurring groups. This is often referred to as a subject or participant variable—a characteristic inherent in the participants that cannot be changed.
Because we are using groups that occur naturally, any differences that we find may be due to the variable of being or not being a Greek member, or they may be due to other factors that we were unable to control in this study. For example, maybe those who like to drink more are also more likely to join a Greek organization.
Once again, if we find a difference between these groups in amount of alcohol consumed, we can use this finding to predict what type of student Greek or non-Greek is likely to drink more. However, we cannot conclude that belonging to a Greek organization causes one to drink more because the participants came to us after choosing to belong to these organizations. In other words, what is missing when we use predictive methods such as the correlational and quasi-experimental methods is control.
When using predictive methods, we do not systematically manipulate the variables of interest; we only measure them. This means that, although we may observe a relationship between variables such as that described between drinking and Greek membership , we cannot conclude that it is a causal relationship because there could be other alternative explanations for this relationship. An alternative explanation is the idea that it is possible that some other, uncontrolled, extraneous variable may be responsible for the observed relationship.
From the Publisher
For example, maybe those who choose to join Greek organizations come from higher-income families and have more money to spend on such things as alcohol. Or maybe those who choose to join Greek organizations are more interested in socialization and drinking alcohol before they even join the organization.
Thus, because these methods leave the possibility for alternative explanations, we cannot use them to establish cause-and-effect relationships. When using the experimental method, researchers pay a great deal of attention to eliminating alternative explanations by using the proper controls.
Because of this, the experimental method allows researchers not only to describe and predict but also to determine whether a cause-and-effect relationship exists between the variables of interest. In other words, this method enables researchers to know when and why a behavior occurs.
Many preconditions must be met for a study to be experimental in nature; we will discuss many of these in detail in later chapters. Here, we will simply consider the basics—the minimum requirements needed for an experiment. The basic premise of experimentation is that the researcher controls as much as possible to determine whether a cause-and-effect relationship exists between the variables being studied.
The idea behind experimentation is that the researcher manipulates at least one variable known as the independent variable and measures at least one variable known as the dependent variable. In our study, what should the researcher manipulate?
If you identified amount of vitamin C, then you are correct. If amount of vitamin C is the independent variable, then number of colds is the dependent variable. For comparative purposes, the independent variable has to have at least two groups or conditions. We typically refer to these two groups or conditions as the control group and the experimental group. In our vitamin C study, the control group does not take vitamin C supplements.
Research Methods and Statistics : A Critical Thinking Approach 4th
The experimental group is the group that receives the treatment—in this case, those who take vitamin C supplements.
Thus, in an experiment, one thing that we control is the level of the independent variable that participants receive. What else should we control to help eliminate alternative explanations? Well, we need to control the type of participants in each of the treatment conditions. We should begin by drawing a random sample of participants from the population.
Actions Shares. Embeds 0 No embeds.
download for others
No notes for slide. Book details Author: Sherri Jackson Pages: Wadsworth Publishing Language: English ISBN Description this book Research Methods and Statistics: If you want to download this book, click link in the last page 5. You just clipped your first slide!
Clipping is a handy way to collect important slides you want to go back to later. Now customize the name of a clipboard to store your clips. Visibility Others can see my Clipboard.
Research Methods and Statistics: A Critical Thinking Approach
Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. Further examining the data set in secondary analyses, to suggest new hypotheses for future study. Documenting and presenting the results of the study. Experiments on human behavior have special concerns.
The famous Hawthorne study examined changes to the working environment at the Hawthorne plant of the Western Electric Company. The researchers were interested in determining whether increased illumination would increase the productivity of the assembly line workers.
The researchers first measured the productivity in the plant, then modified the illumination in an area of the plant and checked if the changes in illumination affected productivity. It turned out that productivity indeed improved under the experimental conditions.
However, the study is heavily criticized today for errors in experimental procedures, specifically for the lack of a control group and blindness. The Hawthorne effect refers to finding that an outcome in this case, worker productivity changed due to observation itself.
Those in the Hawthorne study became more productive not because the lighting was changed but because they were being observed. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis.
In this case, the researchers would collect observations of both smokers and non-smokers, perhaps through a cohort study , and then look for the number of cases of lung cancer in each group. Types of data[ edit ] Main articles: Statistical data type and Levels of measurement Various attempts have been made to produce a taxonomy of levels of measurement. The psychophysicist Stanley Smith Stevens defined nominal, ordinal, interval, and ratio scales.
Nominal measurements do not have meaningful rank order among values, and permit any one-to-one injective transformation. Ordinal measurements have imprecise differences between consecutive values, but have a meaningful order to those values, and permit any order-preserving transformation.Statistical inference, however, moves in the opposite direction— inductively inferring from samples to the parameters of a larger or total population.
For example, if we observed that men channel surf with greater frequency than women, we could then make predictions about how often men and women might change channels when given the chance. Like this presentation? Thinking Like a Scientist The correlation between height and weight, or violent TV and aggressive behavior, is a positive relationship: As one variable height increases, we observe an increase in the second variable weight.
However, the study is heavily criticized today for errors in experimental procedures, specifically for the lack of a control group and blindness. Random assignment helps us to gain control and eliminate alternative explanations by minimizing or eliminating differences between the groups.
As we use more powerful methods, we gain control but lose flexibility. All rights reserved. The psychophysicist Stanley Smith Stevens defined nominal, ordinal, interval, and ratio scales.
How good is that evidence?
- SANDILYAN TAMIL NOVEL PDF
- SAE J517 STANDARD DOWNLOAD
- THE RISE AND FALL OF THE THIRD REICH PDF
- OXFORD ENGLISH FOR ELECTRICAL AND MECHANICAL ENGINEERING ANSWER BOOK
- LA DRAMATURGIE YVES LAVANDIER PDF
- SEELEYS ESSENTIALS OF ANATOMY AND PHYSIOLOGY 8TH EDITION PDF
- LEARNING ANDROID PROGRAMMING PDF
- PARABLE OF THE SOWER EBOOK
- MICROECONOMICS THEORY AND APPLICATIONS BY DWIVEDI FREE EPUB DOWNLOAD
- EBIET G ADE SEPUCUK SURAT CINTA
- BASIC THERMODYNAMICS BY PK NAG EBOOK
- SEDICESIMA LUNA PDF
- STK470-010A EBOOK
- UNEARTHLY SERIES PDF