 Meissuunnitelma on tärkeintä sosiaaliseen ristelun. Joten kun katsotaan ristelun ja katsotaan sinkiltaan, voimme nähdä, että koko pitkän tärkeintä tärkeintä sistemaan, kun olet katsotu ristelun, mitä silti, mitä on sillä ongelmaa ja mitä on sillä ongelmaa, joka on, että mitä on varioita, jotka olet katsotu sillä ongelmaa. Tällä hetkellä tehtäisiin data-kolleikasta ja tehtäisiin data-analyys- ja reportte-resultaamista. Jotain tärkeää on, että kautta sinun lähelläni on tärkeää, mitä sinun samalla on ja mitä sinun lähelläni on. Kun sinun lähelläni on, niin kautta sinun lähelläni on tärkeää. Jos sinun lähelläni ei ole valmis, tai jos sinun lähelläni on tärkeää, niin ei ole mitään, miten on tärkeää tai tärkeää analysointia, joita on tärkeää dataa, sinun lähelläni ei ole kohdeja. Tämä idea on, että haluamme lähelläni vastaamaan tärkeää kautta, mitä me lähelläni olemme. Tällä hetkellä, mitä me voimme lähelläniä, on haluamme kautta, kentärii, kentärii, kentärii, kentärii, kentärii, kentärii, kentärii. Idea on, että kaikki nämä quantit ovat varioita. Idea, että se on varioita, on, että se variaa. Yksi ihmiset ovat toisiaan, mutta yksi ihmiset ovat kohdeja, yksi ihmiset ovat varioita. Yksi ihmiset ovat parempia, yksi companies ovat parempia, ja yksi ihmiset ovat parempia. Idea on, että on vähän varioita, joita me lähelläni lähelläni, ja idea on, että haluaisimme lähelläni tärkeää kentäriiä. Täällä on tärkeä kysymys, kun me lähelläni lähelläni. Yksi kysymys on, mitä me voimme lähelläni. Miten me lähelläni haluamme lähelläni? Miten me lähelläni? Hyvää siltä, että me useamme measurements tape, esimerkiksi temperatuurissa käyttäisiin. Mutta muutamia eri kysymys, jotka voitte uudelleen oppiaa. Ja miten me quantitutteet teille, jotka ovat ei-tysiä quantitutteita, kuin innovativista tai lähelläni? Se on tärkeää, miten me teemme. Nyt kysymyksiä on, mitä me lähelläni teemme. Siinä on yksi, että jokin on ongelmia 5, onko se paljon tai ei ole? Mitä se on tullut? Me olemme tullut ongelmalla ja hoitamme hoitamme hoitamme. Toivottavasti, miten sanoimme, miten olemme hoitamme hoitamme? Tarkoitan, että yksi on huomattu olemme hoitamme hoitamme hoitamme ja olemme, että vihreä vihreä ovat valitettavasti purpose that we are using them for. There are a couple of different, like higher level ways of getting the numbers. Let's look at the research designs by Singleton and Straits. They present four research designs. The first is a laboratory experiment. The idea of a laboratory experiment is that you don't actually measure the key variable that you are studying instead you manipulate it. So laboratory experiments and experimental studies are more about manipulation of things than measurement of things. The remaining three are about measurement and they are different approaches of measurement and to some extent sampling as well. The idea of a survey is that you measure things by asking people. So the subjects provide the numbers. If we study people, their intelligence, then we ask them whether they are smart or not. And if we study companies, we ask people in those companies whether the companies are innovative or not. We can do it also indirectly by asking whether the companies have been successful in producing new products and new services. And then we have the second category is field research. The idea of field research is that we don't ask the subjects. Instead we rate or our research assistant rates or evaluates the subjects and records what happens based on observation and that gives us the numbers. Finally, we can use numbers collected by others. So that's the archival records. So that's basically how we get the numbers. The actual practicalities of how to do that is something that I'll address in other video, but that's the three main ways of getting the numbers. Ask the people, rate yourself, use data collected by somebody else. The next question is what do the numbers tell us and how do we justify the numbers? To answer those questions, we need to understand a little bit about measurement theory, which relates to how the data and the thing being measured are related. To understand measurement theory, we need to understand the concepts of a latent variable. The idea of a latent variable is that an observed variable is that we have two types of variables. The observed variables are variables for which we have case values. So we have a specific number for each individual in our sample. We have a specific number for innovativeness of first company, second company, and so on. These are in model path diagrams. These are presented by these squares. Sometimes measurement measured variables are called indicators or manifest variables, which highlight that their purpose of these measured variables is oftentimes to quantify some unmeasurable or unobservable thing. Latent variable is another kind of variable. The idea of a latent variable is simply that it is a variable for which we don't have the case value. So we know that there is some variation between companies or between people, but we cannot specifically assign numbers to any company. We just know that there is some variation on some attribute or some variable, but we cannot assign the exact numbers. We can estimate these numbers and we can estimate correlations between latent variables, so we can't say what the specific values are. So the difference between latent variable and observed variable are important when we talk about measurement theory and when we talk about models that allow us to test or use or operationalize measurement theory. Then we need to understand a couple of other terms as well. We have to understand the difference between concept, construct and a measure. The idea of a concept is that it's an abstract label for things that we study, and concepts have a reference and often a meaning as well. The idea of a reference is that, for example, if we have a concept of rock, that refers to certain objects that we call rocks. The idea of meaning is that the concept has some kind of meaning as well. So if we say that we have a rock, then people know that, well, we have something that is naturally occurring, it is a hard object, it's probably a size of a couple of fisters, so that's instead of a boulder, which is a larger one, and so on. So the term has some kind of attribute, so the concept has some kind of attribute that are attached to it, that give it meaning. Then a concept can also have a definition, and the idea of a definition is that we have agreed on a specific written definition of what exactly the concept means. When you read papers that develop theory or introduce new constructs, then they quite often define the construct explicitly. I'll get to constructs in a moment. Examples of concepts are persons, for example, and rocks and many other things. So concepts are like abstractions of things that we can observe and study. A construct is a special kind of a concept. It is a concept of a variable, so the idea is that it can vary. So people or organizations can have different degrees of the constructs. You can have different degrees of innovativeness, different amounts of intelligence, and so on. So whereas in these concepts, they can refer generally to just about anything, construct is something that is typically quantifiable. And the reason that these are, because these are quantifiable, we can study constructs using quantitative techniques. Constructs are also latent in the meaning that we cannot assign explicit correct values. We can only observe constructs indirectly. Constructs also can have dimensions. For example, we could have a construct of a person's size with the two main dimensions of height and weight of the person. Then some examples are intelligence. It could have some dimensions, innovativeness. It could have dimensions. So for example, how well you are doing in proc innovation and how well you are doing in service or process innovation and so on. Then measure is the third kind of a variable or a thing that you need to understand. And measure is an observed variable that quantifies one dimension of a construct. If you have multiple dimensions in a construct, then you need at least one measure for each. So it doesn't make any sense to try to quantify a person's size using one number. You need at least two numbers, the height and weight. Examples include IQ test scores, so that's a measure for intelligence. And reading on a mercury column thermometer, which is a measure of temperature. How do these constructs and measures then relate? There are two main approaches. One is a nominalism. The idea is that in nominalism, you basically reject the existence of constructs independently of measurement. And an extreme version of nominalism is operationalism, which says that the construct is simply whatever the measurement process produces. So the construct is defined by the measure. And then realism assumes that the constructs exist independently of measurement. And the purpose of measurement is to discover the true values of the constructs. Most social science research follows the realist approach. So the idea is that there exists something called innovativeness independently of our measurement. We can say that some companies are more innovative than others without measuring those. So that kind of statements make sense if we assume that innovativeness or intelligence exists independently of our measurement of attempt. Then how we actually apply these concepts in practice is that we use the measures as proxies for the constructs. We cannot really observe the constructs directly. So the next best thing is that we build some kind of statistical representation based on our data. And for example, we can just use a number as such. We can take a sum of multiple numbers or we can build a latent variable model and then use the latent variable as a proxy for the construct. So we use these empirical representations constructed based on our data as proxies for the constructs. Assuming that the empirical representation is a perfect representation of the construct. That is of course something that is hardly ever exactly correct, but we have to justify that it is a good enough approximation. So that's the idea of a proxy. So instead of using the construct when we study something, we use the measure as a stand-in for the construct. Summary of these key concepts. We have the constructs, construct is a concept. So it's a variable that exists in principle. It can have some definition almost always as a definition. We can say that some companies or some individuals are higher on the construct than others and we cannot observe it directly. Then observed variables are specific numbers for each subject or a case that we have collected somehow. The idea is that these measures, if we take the realist perspective, the idea is that these are, the variation in these measures is caused by the variation in the construct. For example, people's IQ scores differ because their intelligence differs. So that's the reason why there's variation in the data is that there's variation in the construct. Thermometer changes its value because the temperature outside is different from one day to another. So that's the idea of realist perspective to measurement, which I will be using in these videos.