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Differences and similarities between qualitative and quantitative
Differences and similarities between qualitative and quantitative
Differences and similarities between qualitative and quantitative
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Introduction to variables in statistics tutor:
The variable which is available in the statistics it is called as statistical variable. It is a feature that may acquire choice in adding of one group of data to which a mathematical enumerates can be allocated. Some of the variables are altitude, period, quantity of profit, region or nation of birth, grades acquired at school and category of housing, etc,. Our statistics tutor defines the different types of statistics variables and the example of these types. Our tutor helps to you to know more information about the variables in statistics.
Variables in statistics tutor:
Let us, see the different types of variable used in statistics and the uses of these types. There two kinds of variable used in statistics. They are,
Statistical variable 1: Qualitative variables
Statistical variable 1: Quantitative variables
These two kinds are used for various uses based on the statistics. Also, these types are divided into number of categories and which is used to various uses.
Explanation of...
Except as provided in subparagraph [1] (C) and (D), the predominant use of any property shall be determined based on—
A researcher determines that 42.7% of all downtown office buildings have ventilation problems. Is this a statistic or a parameter; explain your answer.
2. a) The research design used in this study is the case study design. It is classified
12). These are the most common methods that are being used. The difference between qualitative and quantitative methods concerns how the data are collected, where basically qualitative data focus on words while quantitative focus on numbers (Denscombe, 1998, p. 173-174).
First, all data have both an objective and a subjective component. Numbers can be easily assigned to all qualitative data (such as open-ended questions in surveys), and any number obtained by a quantitative study is interpreted using a subjective or qualitative judgment. Second, using differen...
In order to have a successful, reliable experiment you need sufficient data and evidence, reliable research, variables to test and a follow – up experiment. There are several types of variables you need to do an experiment. An independent variable is the manipulated experimental factor that is changed to see what the effects are. A dependent variable is the outcome. This factor can change in an experiment in reaction to the changes in the independent variable. An experimental group is the group of participants that are exposed to the change that the independent variable represents. The control group is participants who are treated in the same way as the experimental group except for the manipulated factor which is the independent variable (King 24). Proper data, evidence and research is also needed so the experiment turns out correctly and you know what you are testing. A follow – up experiment is not required, however it helps the validity of the conclusion of the experiment. Validity is “the soundness of the conclusions that a researcher draws from an experiment” (King 25). Conducting a follow – up experiment will help researchers and people alike see if the experiment worked properly, continues to help people and see how participants are doing after the experiment is over.
A parameter is used in inferential statistics and is used to describe the scores of a population—letters of the Greek alphabet symbolizes a parameter. An estimate in statistics is a value, which was produced by the sample, and inferred to be the value of the
The scientific findings needs to be used are the following, variable which is a logical set of attributes. The attributes is a characteristic or quality of something. For example, the attributes towards my study, would be the ages of both sex genders from college students and parent 's. Due to the fact, if there 's a chance of inheriting alcohol behavior to consume during the adolescence to young adulthood. "The implication of the level of measurement would be analyses require a minimum level of measurements and some variables can be treated as multiple level of
which I had not used before. If I had not done this, I would have got
Independent variable (pg. 39) – a type of variable that is controlled by the experimenter, and comes before the dependent variable. An example of an independent variable in a study would be the amount of time played by a college football player.
What is the difference between a.. Makes inter-firm comparison possible Ratios analysis also makes possible comparison of the performance of different divisions of the firm. The ratios are helpful in deciding whether their efficiency or otherwise in the past and likely performance in the future. 5. What is the difference between a'smart' and a'smart'? Help in investment decisions It helps in investment decisions in the case of investors and lending decisions in the case of bankers etc.
The Collier Encyclopedia’s definition for probability is the concern for events that are not certain and the reasonableness of one expectation over another. These expectations are usually based on some facts about past events or what is known as statistics. Collier describes statistics to be the science of the classification and manipulation of data in order to draw inferences. Inferences here can be read to mean expectations, leading to the conclusion that the two go hand in hand in accomplishing what mankind has tried to accomplish since the beginning of time – predicting the future. It is the notion of science that this is the most accurate way to predict events yet to occur and this has lead to it being the most widely accepted “fortune telling'; tool in the world today.
The second dimension is that of the nature of data used in the study. Data used in empirical studies can be numeric, textual or a combination of both. When the basic data used in an empirical study consist of words, the research is classified as qualitative, whereas if the data used are numeric, the research is classified as quantitative. A research design may also combine quantitative and qualitat...
c. Statistical Design: It concerns with the question of how many items are to be observed and how the information and data gathered are being
Whether or not people notice the importance of statistics, people is using them in their everyday life. Statistics have been more and more important for different cohorts of people from a farmer to an academician and a politician. For example, Cambodian famers produce an average of three tons or rice per hectare, about eighty per cent of Cambodian population is a farmer, at least two million people support party A, and so on. According to the University of Melbourne, statistics are about to make conclusive estimates about the present or to predict the future (The University of Melbourne, 2009). Because of their significance, statistics are used for different purposes. Statistics are not always trustable, yet they depend on their reliable factors such as sample, data collection methods and sources of data. This essay will discuss how people can use statistics to present facts or to delude others. Then, it will discuss some of the criteria for a reliable statistic interpretation.