Quantitative research can be represented numerically, whereas Qualitative data cannot.
Quantitative research is more interested in hard data procured through things like surveys, polls, and censuses. This type of research is interested in things like the percentage of people interviewed that agree with one statement versus another, the number of people in a culture that belong to a certain organization, or how many people in a country speak the native language versus how many are bilingual or only speak a foreign language. This method of research usually requires a large random sample group. It is totally concerned with the hard evidence(quantity) through statistics and recorded happenings, participants, and locations.
Qualitative research is typically descriptive, or anecdotal, and does not lend itself to the analysis of quantitative data. Qualitative research is in-depth research that seeks to understand why something happens the way it does. In anthropology, qualitative research includes participating as well as observing. It often crosses disciplinary boundaries and strays from a single subject, or variable being studied. Due to the specific rapport required to obtain qualitative data, it generally requires a smaller sample size.
Made popular during the late 18th century, this was the primary anthropological method used until the 1970s. It is based around the central idea of positivism, a theory saying that theology and metaphysics are earlier imperfect modes of knowledge and that positive knowledge is based on natural phenomena with their properties and relations as verified by the scientific method. The main goal of a positivist approach is to produce objective knowledge, which is knowledge about humanity that is true for all people in all times and places. The ideal positivist approach would occur with a physical scientist in a lab, producing concrete results. Anthropologists adapted this method to their own use by testing hypotheses in different cultures under similar conditions. This method was very successful in recording previously unknown data about different peoples, but it was often objective facts about a way of life in which the people of the culture at question were regarded more as lab subjects than actual human beings. Eventually this method was adapted into the reflexive method, to better demonstrate the relationships that exist within communities and the anthropologists own interactions with the informants.
The positivist approach requires the use of the scientific method. A researcher makes an observation about a social behavior or condition, constructs a hypothesis as to the reason or outcome of the observation, tests the hypothesis and then analyzes the results. 
Spradley describes ethnography as different from deductive types of social research in that the five steps of ethnographic research: selecting a problem, collecting data, analyzing data, formulating hypotheses, and writing. All five steps happen simultaneously (p. 93-94).
In his book, Spradley describes four types of ethnographic analysis that basically build on each other. The first type of analysis is domain analysis, which is “a search for the larger units of cultural knowledge” (p. 94). The other kinds of analysis are taxonomic analysis, componential analysis, and theme analysis.
All of Spradley’s theories about ethnographic analysis hinge on his belief that researchers should be searching for the meaning that participants make of their lives. These meanings are expressed through symbols, which can be words, but can also be nonverbal cues. However, because this book is about analyzing interviews, Spradley focuses on analyzing the spoken words of the participants. He explains that words are symbols that represent some kind of meaning for an individual, and each symbol has three parts: the symbol itself, what the symbol refers to, and the relationship between the symbol and the referent. Thus, the word computer can be a symbol. It refers to many things, including an individual's own personal computer. Thus, a computer is a kind of computer in the mind, or the idea of a computer, and this shows the relationship between the symbol (computer) and the referent (an actual physical computer).
A domain is a “symbolic category that includes other categories”. The category of computers is a domain that includes not only a laptop, but all the Dells, Toshibas, iMacs, and IBMs in the world. These all share the same relationship because they are all kinds of computers. There are three elements to a domain. First, the cover term, which in this example is the word “computer”. Second, there are included terms, which are all the types of computers just listed. Finally, there is the single, unifying semantic relationship, which is the idea that “X, Y, and Z are all kinds of A”.
When anthropologists complete a domain analysis, they are gaining an understanding of how people place objects within different domains. In other words how does a person, family, or culture categorize the world around them. This information can be gathered is several ways. Strict inclusion ("what is a Macbook, a computer), Domain analysis, and questioning the categorization are methods of domain analysis. To revert to the previous example, if you agree that Macs are kinds of computers, you could test this hypothesis by making a question out of this semantic statement; “Are there different kinds of computers?” You could ask a participant, and based on their answer, you would know if the cover term, included terms, and semantic relationship that you identified were correct. You could then probe with more questions like, “Why are Macs a kind of computer?” or “In what way are Macs a kind of computer?”
Taxonomic Analysis is a search for the way that cultural domains are organised. Building upon the first type of analysis, this form of research is best defined as the classification of data in form x is a kind of y (D'Andrade, 92). Used largely for the organization and grouping of plant and animal species, the taxonomic analysis is not focused on the features of an organism but rather the variable genetic differences that define them. Taxonomic Analysis usually involves drawing a graphical interpretation of the ways in which the individual participants move, form groups, and pattern the structure of a conversation. For example, scientists can refer to the common chimpanzee using the taxonomy pan troglodyte ( which is the ITIS report that has qualifications of all known mammals) and make specific references to that species without fear of error in their classification and use of data.