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Research Methods Cheat Sheet by

Research methods paper

Types of data

Primary data
Data collected by the researcher themselves i.e. experi­ments / surveys / observ­ations.
- Relevant Inform­ation - Can Control method­ology
- Time Consuming - Can be costly dependant on the methods used
Secondary data
Data collected by other people & organi­sations
- Already gathered so quicker - Usually cheaper to access
- Inform­ation may be old and inaccurate - Questi­onable whether it can be applied
Quanti­tative data
Numerical, statis­tical inform­ation that is objective. Answers factual questions instead of giving reason­ings.
- Best for repres­ent­ati­veness and genera­lis­ability - Broader study - greater number of subjects
- Harder to analyse and give reasonings - Can't explore why
Qualit­ative data
Type of data that is focused around opinion, feelings and why something is happening. Complex data and harder to analyse. Subjective Data.
- Detailed inform­ation that explores reason­ings- Based on human experience which gives better validity
- Longer process to analyse the data as it all varies due to subjective nature If not careful,- researcher can have a negative impact on the results - behaviour

Positivism vs interp­ret­ivism

POSITIVSM - Theory appraoch based on natural and factual causes - idea surrounds object­ivity and positi­vists want statis­tical, quanti­tative data that reveals the truth.
INTERP­RETIVSM - Approach which tries to see explan­ations from sujects perspe­ctive. They want Verstehen (Meaning) and qualit­ative data with reasons as to why something happened.
Preferred research methods: Quanti­tative, Offical Statis­tics, Social Surveys, / Unstru­ctured Interviews / Questi­onn­aires
Preferred research methods: Qualit­ative, Personal Documents, Partic­ipant Observ­ation, Unstru­ctured Interviews

Stages of research

1. Choice of topic
Deciding whether the research will focus on • social problems • sociol­ogical problems
They need to know what they’re studying
2. Aim
Consid­ering the main research goal in their study
It is important to have a research goal
3. Operat­ion­alise research values
Breaking down the hypothesis or aim into concrete values that can be measured
Precise measur­ement of social phenomena cannot occur without it and it allows others to replicate your research
4. Choose target population
Choosing people with the charac­ter­istics you want to research
It is important to have a defined research population

Stages of research (cont)

5. Choose sampling method
Choosing between random and non-random sampling
The sampling method is crucial to ensure the sample is genera­lisable
6. Choose research method
Choosing between qualit­ative and quanti­tative methods
It is important to choose the correct research method for your aims
7. Conduct research
Carry out your chosen method on your sample
Carrying out the method correctly improves the validity of your data
8. Analyse data
Looking for patterns in the data
Spotting patterns correctly can allow for new discov­eries

Ethics and access

1.Informed consent – research subjects should be fully aware of the study and its aims
2. No deceit – sociol­ogists should not keep inform­ation or lie about the purpose of the study
3. Privacy is kept – the privacy of the research subjects should be safegu­arded as much as possible
4. Protection from harm – protection from physical harm, emotional harm and profes­sional harm
5. No illegal or immoral behaviour – sociol­ogists need to avoid situations where they could be drawn into illegal behaviour
Access – some groups have the power to resist sociol­ogists such as the rich and powerful therefore, data on these groups is usually secondary data using statis­tics.
Gateke­eping – A gatekeeper has contact with the research subjects and will check any interview for sensitive subjects
Funding – This may affect the research method, if lots of funding is available the researcher may employ a team and be able to complete in-depth interv­iews, if funding is low the researcher may need to choose a cheaper option such as postal questi­onn­aires.

Triang­ulation strengths and weaknesses

• The methods cancel out the disadv­antages and allow sociol­ogists to guarantee validity
• Can be expensive and time-c­ons­uming depending on the methods chosen
• Can reveal new inform­ation and hypotheses
• The methods have to complement one another and cancel out the disadv­antages
• Provides a better unders­tanding of the problem
• More skills are needed to analyse the vast amounts of data
 

Sampling methods

Random: names are picked randomly from a list
• Lack of bias as it is randomly chosen • Simplicity as there are no additional steps
• Time-c­ons­uming and expensive due to the inform­ation needed • Sample selection bias can occur when a sample chosen is not repres­ent­ative
System­atic: randomly choosing a number and picking every 10th e.g. 7,17,27 e.c.t
• Most repres­ent­ative as it relies in statis­tical odds • It is easy to execute and understand • Provides control
• Large sample needed to ensure that statis­tically it is likely to be repres­ent­ative • Not truly random • by chance might get same results.
Strati­fied: dividing the population into sampling frames and using systematic sampling
• Relatively small sample • can be used with confidence that it's still repres­ent­ative • Requires a smaller sample than random sampling
• Requires sampling frame which includes details of signif­icant charac­ter­istics of population being studied • Timely • May take a lot of resear­chers
Snowball: When one person leads you to another
• Used mainly with groups who are hard to identify or access (e.g. criminals) • The process is cheap, simple and cost-e­ffi­cient. • This sampling technique needs little planning and fewer workforce compared to other sampling techni­ques.
• Very unlikely to be truly repres­ent­ative since based on people who have contact with one another • Repres­ent­ati­veness of the sample is not guaran­teed. The researcher has no idea of the true distri­bution of the population and of the sample. • Sampling bias is also a fear of resear­chers when using this sampling technique. Initial subjects tend to nominate people that they know well. Because of this, it is highly possible that the subjects share the same traits and charac­ter­istics, thus, it is possible that the sample that the researcher will obtain is only a small subgroup of the entire popula­tion.

Sampling methods (cont)

Volunteer: Partic­ipants becoming part of a study because they volunteer when asked or in response to an advert
• More ethical because partic­ipants have approached researcher • May have an interest in the subject so they are less likely to give biased inform­ation • Easy to do
• Could take a long time to get enough people to do experiment • Rules out certain occupa­tions and types of people - unrepr­ese­ntative • Expensive to place advert
Quota: Like stratified sampling but the researcher decides how many people in each group are involved
• Advantages of stratified random sampling but can be conducted without variables being available from sampling frame • Useful for groups with no sampling frame • Common in opinion polls
• Access­ibility of potential respon­dents affects their chances of being included in the sample. • May be less repres­ent­ative than random and stratified random sampling • Results may be distorted and not repres­ent­ative
Purposive: Involves resear­chers choosing indivi­duals or cases from a particular place that reflect the nature of their research
• Tends to be easiest and quickest way of collecting a sample • may lead to a good response rate • Is affordable
• Makes no attempt to be truly repres­ent­ative, so can't generalise from the findings • Is open to bias • It is vulnerable to researcher judgement
Opport­unity: Taking the sample from people who are available at the time the study is being carried out and fit the criteria you're looking for
• Less time consuming • Easy to use • Cheap
• Biased • Cannot be genera­lised • Researcher has control over selection so may be subjective to their views

Statistics strengths and weaknesses

• They are often extremely easy and cheap to access as they are usually online
• They may not be repres­ent­ative of the wider population as they are collected by indepe­ndent bodies
• They are often up-to-date so give sociol­ogists an unders­tanding of modern behaviour
• They can be politi­cally massaged to make a country look better
• They often form the basis of hypotheses that motivate research
• They tell us very little about the human stories that underpin them so are disliked by interp­ret­ivists
 

Questi­onnaire strengths and weaknesses

• Used for reaching larger and more repres­ent­ative samples as it can be given to hundreds of people
• Many people do not respond to questi­onn­aires which can cause low response or no response and can undermine validity
• Postal questi­onn­aires are useful when the research population is geogra­phi­cally spread out
• The questions can be biased or leading
• They are cheaper and less time-c­ons­uming than other methods
• It is difficult to motivate people to return postal questi­onn­aires

Structured interviews strengths and weaknesses

• Positi­vists regard the method as scientific as it primarily produces qualit­ative data
• They are artificial and not in everyday life so may give false inform­ation as they are suspicious
• The use of closed questions creates lots of quanti­tative data which can be converted into charts
• They are inflexible so sociol­ogists cannot focus on other things if they hear something intere­sting
• Because of the interview schedule, structured interviews are quick and can allow for a larger sample
• Interp­ret­ivists believe they do not produce true data

Unstru­ctured interviews strengths and weaknesses

• They allow the researcher to build rapport which allows the partic­ipants to open up more which can enrich data
• Unstru­ctured interviews create a lot of data and require the researcher to be selective of what they publish
• Unstru­ctured interviews allow the researcher to explain more about the research so they are useful for resear­ching unknown groups
• The qualit­ative data is difficult to analyse as there are no pre-coded answers
• They provide richer, more detailed data which is highly valid
• Studies that use unstru­ctured interviews use less partic­ipants which undermines the repres­ent­ati­veness to positi­vists

Semi-s­tru­ctured interview

• Allows the researcher to explain the research and gain informed consent so is ethical
• It is time consuming and expensive compared to other methods
• Interp­ret­ivists see the data as valid as it allows the researcher to understand the world through the partic­ipants eyes
• Not reliable as it is hard to replicate
• Feminists argue this method gives women an opport­unity to express how they really feel
• Positi­vists reject this see it as unscie­ntific this method lacks object­ivity and reliab­ility and fails to produce repres­ent­ative data that can be genera­lised to the wider popula­tion.

Observ­ations strengths and weaknesses

• The researcher sees things through the eyes of the group so the researcher experi­ences ‘verst­ehen’ or empathy which results in highly valid data
• Overt forms of research are subject to the researcher effect which may result in the group acting less naturally as the researcher is there which undermines validity
• Often what people say and what they do is different, people may lie or not be aware of their actions in interviews
• Some observers get too attached to the research group and show bias towards them reporting the data incorr­ectly and losing object­ivity
• Observ­ation can be supple­mented with unstru­ctured interviews to add to the validity
• Covert observ­ation is highly unethical

Ethnog­raphy strengths and weaknesses

• Ethnog­raphy is usually long-term and in-depth as well as qualit­ative so produces lots of rich data
• It usually is a study of a specific group and is therefore not repres­ent­ative of wider society
• It allows the researcher to achieve verstehen with the group they study which means they are more likely to open up
• It is subjective to the resear­cher’s opinions so could be biased
• The rapport built means it is high in validity
Positi­vists dislike the data as it is not reliable or analysable

Content analysis strengths and weaknesses

• It is very cheap as all that is needed is media products
• It can be very time-c­ons­uming
• It is a compar­ative analysis that can be longit­udinal
• It is very subjective as the categories depend on what the researcher thinks is important
• Quanti­tative content analysis is reliable as it can be repeated by other sociol­ogists
• Sociol­ogists have been accused of analysing text out of context
       

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