Presentation on theme: "Developing the Research Question"— Presentation transcript:
1 Developing the Research Question Soc 3306a Lecture 3Developing the Research Question
2 Research questions and objectives (adapted from Fig. 3.1 Blaikie 2000)
3 ‘What’ and ‘Why’ questions Descriptive questionsWhat types of people are involved?What is their characteristic behaviour?What are consequences of their behaviour?Why?To find causes for or reasons whyWhy do they think/act this way?Why does this behaviour have particular consequences?
4 Using statistics to answer research questions Statistics are mathematical tools used to organize, summarize, and manipulate data.Data gathered through survey items and are the scores on the variables used in a statistical analysis.Data is simply information expressed as numbers (quantitatively).4
5 Statistical Applications Two main statistical applications:Descriptive statisticsInferential statistics5
6 Descriptive Statistics Univariate descriptive statistics summarize the information on one variable at a time.%, mean, standard deviation, histogramBivariate descriptive statistics summarize the relationship (i.e. describe the strength and direction) of the relationship between two variablesGamma, correlation coefficient, scatterplot6
7 Descriptive Statistics Multivariate descriptive statistics describe the relationships between three or more variables.Multiple correlation, two-way ANOVA, multiple regression.Can describe the complex and multi-layered relationships in the social world.7
8 Inferential Statistics Can use to make inferences from a random sample statistics in order to generalize the results to a population.Can also use to test for significant differences in group means or proportions.This is “hypothesis” testingZ or T-tests, one-way ANOVA (F), Chi-square statistic8
9 Variables…. Used to calculate statistics Are concepts in numerical form that can vary in valueHave traits that can change values from case to case.Examples:Age, Gender, Race, Social class change for different individuals in a survey study9
10 Case The entity from which data are gathered Can be individuals, groups, organizations, nations etc.The “unit of analysis”In the datasets you will be using, each case is an individual survey respondent10
11 Reliability and Validity Validity = truthfulness of a measureIs it measuring what the researcher thinks it is measuring?Reliability = the consistency or dependency of a measureDoes the measure consistently give the same results?Reliability can be assessed numerically with statistics like Cronbach’s alpha
12 Measurement ErrorSystematic: the measure (ie survey item) is flawed or distorted and does not reflect a respondent’s true attitude or behaviourthis is validityRandom: lack of agreement between repeated uses of a measureThis is reliabilityPrecision error: related to the “level of measurement” of a variable
13 Important aspects of Quantitative Variables: a) Independent vs dependent variablesAntecedent (control) and Interveningb) Continuous vs. discrete categoriesMutually exclusive and exhaustive attributesc) Levels of measurement:nominalordinalinterval/ratio
14 Independent and Dependent Variables In causal relationships:CAUSE EFFECTindependent variable X dependent variable YIndependent variables (“causal” or “explanatory”) are those that are manipulated. Can use more than one in a multivariate analysis (X1, X2, X3….)Dependent (“outcome” or “response”) variables are measured for variation in response to X.14
15 Discrete and Continuous Discrete variables are measured in units that cannot be subdivided.Example: GenderContinuous variables are measured in a unit that can be subdivided infinitely.Example: Age15
16 Level Of MeasurementThe mathematical quality of the scores of a variable.Nominal - Scores are labels only, they are not numbers.Ordinal - Scores have some numerical quality and can be ranked.Interval-ratio - Scores are numbersAll mathematical operations possible.Most “precise” level of measurement16
17 Survey items as variables Survey items are questions used to measure demographic, behavioural, or attitudinal aspects of individuals (cases)Each item is a variableResponse categories should have mutually exclusive and exhaustive attributesItems can be combined to create composite measures (i.e. Index, Scale)
18 Using one of the datasets to answer ‘what’ and ‘why’ Look at the variables in one of the datasets available for your research to see which variables might be suitable to answer ‘what’ and ‘why’ questionsExamine the actual questions asked and the level of measurement of answersWhich variables are of interest to you?What type of questions can you ask?
19 Hypothetical problem statement: (Uses variables from a 2007 CCHS dataset) “How is overall health affected by the food choices that are made?”Is this problem important? Why?Other questions related to this problem:What factors determine one’s food choices?What are the consequences of the food choices people make?What role do doctor/dentist visits play?
20 Other related questions What age groups or gender make healthier food choices?What are the consequences of less healthy food choices?What group is more likely to visit the doctor/dentist regularly?Does ability to chew affect food choices and consequently, overall health?
21 Identify specific variables in a dataset that can be used to solve the problem…. Respondent’s AgeRespondent’s GenderConsumption of fruit (index)Consumption of vegetables (index)# of doctor, dentist visitsRespondent has trouble chewingRespondent’s overall health status
22 Relations Between Variables Hypothesis: a statement that describes the relationship between two or more variables.Null hypothesis: What is actually tested in a statistical testAlternate hypothesis: The research hypothesis. “Rejection” of the null builds up evidence for the research hypothesis
23 Testable HypothesesHypotheses are stated in terms of your chosen specific variables:Higher consumption of fruit and vegetables leads to better overall health (main hypothesis)Ability to chew increases the likelihood of higher fruit/vegetable consumption# of dentist visits is related to the ability to chew
24 The Causal Model (See Figure 4.7 in Gray and Guppy) Possible model to answer research questions and test hypotheses above:DVOverall Health StatusMain IVConsumption of Fruit and VegetablesAV (Control)GenderAV# of Dentist visitsAntecedent Variable (control)AgeIntervening variableDoctor visitsAbility to chew