3 I’s

• individual interview


  These are ideas or categories that emerge from a grouping of lower-level data points
• questionnaires


  It can be open or closed-ended questions
• observation


  It deals with an actual encounter with respondent particular activities of the day.
• survey


  These are series of questions and other prompts for the purpose of gathering information from respondents
• themes


  It is a conversation between the interviewer and the interviewee to gather relevant information using prepared questions.
• data


  factual information [as measurements or statistics] used as a basis for reasoning, discussion, or calculation.
• data analysis


  a process of understanding data or known facts or assumptions serving as the basis of any claims or conclusions you have about something.
• bias


  defined as any tendency which prevents unprejudiced consideration. In research, bias occurs when "systematic error [is] introduced into sampling or testing by selecting or encouraging one outcome
• plagiarism


  is presenting someone else's work or ideas as your own, with or without their consent,
• intellectual honesty


  is honesty in the acquisition, analysis, and transmission of ideas.
• content analysis


  This is one of the most common methods to analyze qualitative data. It is used to analyze documented information in the form of texts, media, or even physical items.
• narrative analysis


  This method is used to analyze content from various sources, such as interviews of respondents, observations from the field, or surveys.
• framework analysis


  This is more advanced method that consists of several stages such as familiarization, identifying a thematic framework, coding, charting, mapping and interpretation.
• discourse analysis

  used to analyze interactions with people.
• grounded theory

  using qualitative data to explain why a certain phenomenon happened. 
• data preparation

  The first stage of analyzing data
• data preparation

  aim is to convert

  raw data into something meaningful and readable. 
• data validation

   find out, as far as possible, whether the data collection was done as per the pre-set standards and without any bias.
• fraud

  "to infer whether each respondent

  was

  actually interviewed or not.
• screening

  to make sure that respondents were chosen as per the research criteria.
• procedure

  to check whether the data

  collection

  procedure was duly followed.
• completeness

  to ensure that the interviewer asked the respondent all the questions, rather than just a few required ones.
• data editing

  basic data checks check for outliers, and edit the raw research data to identify and clear out any data points that may hamper the accuracy of the results.
• data coding

  This is one of the most important steps in data preparation. It refers to grouping and assigning values to responses from the survey.
• descriptive statistics

  also known as descriptive analysis
• descriptive statistics

  is the first level of analysis. It helps researchers summarize the data and find patterns.
• mean

  numerical average of a set of values.
• median

  midpoint of a set of numerical values.
• mode

  most common value among a set of values.
• percentage

  used to express how a value or group of respondents within the data relates to a larger group of respondents.
• frequency

  the number of times a value is found.
• range

  the highest and lowest value in a set of values.