How are qualitative and quantitative research methods similar

how to write quantitative research design and how to use quantitative research design and how to write quantitative research questions present quantitative research findings
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Published Date:01-07-2017
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Introduction to Statistics and Quantitative Research MethodsPurpose of Presentation • To aid in the understanding of basic statistics, including terminology, common terms, and common statistical methods. • To help those interested in research feel more comfortable with statistics. • To encourage potential researchers to undertake research projects to facilitate the production of knowledge.Statistics Defined • Statistics is the science and practice of developing human knowledge through the use of empirical data expressed in quantitative form. It is based on statistical theory which is a branch of applied mathematics. Within statistical theory, randomness and uncertainty are modelled by probability theory (Wikipedia Encyclopedia).What is statistics? • The collecting, summarizing, and analyzing of data. • The term also refers to raw numbers, or “stats”, and to the summarization of data. • Example: Frequencies Statistics humour • Why is a physician held in much higher esteem than a statistician? • A physician makes an analysis of a complex illness whereas a statistician makes you ill with a complex analysisResearch Methods • Research is structural. There are basic steps depending on Draw Conclusions the subject matter and researcher. Analyze Data This step is • It is also possible to conduct minimized Collect Data research using pre-collected when using data, this is called secondary secondary data analysis. There are data Research Design many advantages to using secondary data, and Fraser Develop Research Question Health has a large number of data sets available for analysis.Æ Basic Steps • The following are the basic steps of most research. • 1) Develop a research question • 2) Conduct thorough literature review • 3) Re-define research question hypothesis • 4) Design research methodology/study • 5) Create research proposal • 6) Apply for funding • 7) Apply for ethics approval • 8) Collect and analyze data • 9) Draw conclusions and relate findings Research begins when there is a question. • Different kinds of questions: Descriptive: Inferential: How many men work Does having a science at Fraser Health? degree help students learn statistical How many hours a week concepts? do employees spend at their desks? What risk factors most predict heart disease?Types of Statistics • Descriptive Statistics: describe the relationship between variables. – E.g. Frequencies, means, standard deviation • Inferential Statistics: make inferences about the population, based on a random sample. Variables • In research, the characteristic or phenomenon that can be measured or classified is called a variable. There are 4 levels of variables: • Nominal • Ordinal • Interval • Ratio Levels of Data • Nominal= categorical • E.g. Apples and pears, gender, eye colour, ethnicity. • Data that is classified into categories and cannot be arranged in any particular order. – Nominal=Categorical=Dichotomous • Ordinal= data ordered, but distance between intervals not always equal. E.g. Low, middle and high income, or rating a brand of soft drink on a scale of 1-5. • Interval= equal distance between each interval. E.g. 1,2,3. Arbitrary zero point (ex. Fahrenheit scale for temperature - temperature does not cease to exist at 0 degrees. • Ratio= similar to interval scale, but has true zero point E.g. Weight, salary (0=0). Types of Variables • Variables can be classified as independent or dependent. • An independent variable is the variable that you believe will influence your outcome measure. • A dependent variable is the variable that is dependent on or influenced by the independent variable(s). A dependent variable may also be the variable you are trying to predict.ÆÆ Æ Æ Types of Variables • An intervening variable is the variable that links the independent and dependent variable Independent Variable Intervening variable Dependent variable E.g. Educational level Occupational type Income level • A confounding variable is a variable that has many other variables, or dimensions built into it. • Not sure what it contains or measures. • For example: Socio Economic Status (SES) – How can we measure SES? Income, Employment status, etc. – Need to be careful when using confounding variables… Æ Æ Æ Æ Example A researcher wants to study the effect of Vitamin C on cancer. Vitamin C would be the independent variable because it is hypothesized that it will have an affect on cancer, and cancer would be the dependent variable because it is the variable that may be influenced by Vitamin C . Independent Variable Direction of Affect Dependent Variable Vitamin C Increase or Cancer decrease of certain affect5 minute group exercise 3 Questions: For each question: • What is the dependent variable in this study? • What is the independent variable? • What is the level of data? 5 minute group exercise 1) Researcher Purple wants to examine if a women's consumption of calcium is related to large foot size. Calcium is measured in milligrams, and foot size is measured in centimetres. Researcher Purple hypothesizes that calcium affects foot size. 2) Researcher Orange wants to know if a man’s consumption of orange juice is related to an increase in male pattern baldness. Consumption of orange juice is measured in millilitres, and male pattern baldness is measured on a scale of 1-3 (1=totally bald, 2=some balding, 3=no balding). Researcher Orange hypothesizes that orange juice affects male pattern baldness. 3) Researcher Blue wants to know if pet type has a relationship with happiness. Pet type is measured on a scale of 1-5 (1=cat, 2=dog, 3=bird, 4=fish, 5=other). Happiness is measured on a scale of 1-3 (1=not happy, 2=somewhat happy, 3=very happy). Researcher Blue hypothesizes that pet type will affect level of happiness.Back to stats….. Statistics made simple…Descriptive Statistics Defined Mean What is a mean? • The sum of all the scores divided by the number of scores. • Often referred to as the average. • Good measure of central tendency. • Central tendency is simply the location of the middle in a distribution of scores.The Mean “A statistician is someone who can have his head in an oven and his feet in ice, and say that on the average he feels great.” • The mean can be misleading because it can be greatly influenced by extreme scores (very high, or very low scores). • For example, the average length of stay at a hospital could be greatly influenced by one patient that stays for 5 years. • Extreme cases or values are called outliers. • Sometimes the median may yield more information when your distribution contains outliers, or is skewed (not normally distributed). • What is a median? Median A median is the middle of a distribution. • Half the scores are above the median and half are below the median. • How do I compute the median? • If there is an odd number of numbers, the median is the middle number. For example, the median of 5, 8, and 11 is 8. • If there is an even number of numbers, the median is the mean of the two middle numbers. The median of the numbers 4, 8, 9, 13 is (8+9)/2 =8.5.

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