When responding to a Likert questionnaire item, respondents specify their level of agreement to a statement. The scale is named after its inventor, psychologist Rensis Likert.
Chi-square test Video transcript I'm thinking about buying a restaurant, so I go and ask the current owner, what is the distribution of the number of customers you get each day? And he says, oh, I've already figure that out. They're closed on Sunday. I obviously am a little bit suspicious, so I decide to see how good this distribution that he's describing actually fits observed data.
So I actually observe the number of customers, when they come in during the week, and this is what I get from my observed data. So to figure out whether I want to accept or reject his hypothesis right here, I'm going to do a little bit of a hypothesis test.
So I'll make the null hypothesis that the owner's distribution-- so that's this thing right here-- is correct. And then the alternative hypothesis is going to be that it is not correct, that it is not a correct distribution, that I should not feel reasonably OK relying on this.
It's not the correct-- I should reject the owner's distribution. Or another way of thinking about it, I'm going to calculate a statistic based on this data right here. And it's going to be chi-square statistic.
Or another way to view it is it that statistic that I'm going to calculate has approximately a chi-square distribution. If I don't get that, if I say, hey, the probability of getting a chi-square statistic that is this extreme or more is greater than my alpha, than my significance level, then I'm not going to reject it.
I'm going to say, well, I have no reason to really assume that he's lying. So let's do that. So to calculate the chi-square statistic, what I'm going to do is-- so here we're assuming the owner's distribution is correct.
So assuming the owner's distribution was correct, what would have been the expected observed? So we have expected percentage here, but what would have been the expected observed? So let me write this right here.
I'll add another row, Expected. Now to figure out what the actual number is, we need to figure out the total number of customers.
So let's add up these numbers right here. So we have-- I'll get the calculator out. So we have 30 plus 14 plus 34 plus 45 plus 57 plus So there's a total of customers who came into the restaurant that week. So let me write this down. So this is equal to-- so I wrote the total over here.
Ignore this right here. I had customers come in for the week. So what was the expected number on Monday?To review the student on the concepts and processes necessary to successfully answer questions over Mendelian genetics and chi square analysis problems.
Standards Mendelian genetics and chi square analysis are addressed in the topic outline of the College. Bullying and cyberbullying in Portugal: Validation of a questionnaire and analysis of prevalence Bullying and cyberbullying victimization frequency, percentage of victimization, by gender and chi-square .
A variety of options for analyzing Likert scale data exist including the chi square statistic. The chi square statistic compares survey respondents' actual responses to questions with expected answers to assess the statistical significance of a given hypothesis.
A chi-squared test, also written as χ 2 test, is any statistical hypothesis test where the sampling distribution of the test statistic is a chi-squared distribution when the null hypothesis is true. Without other qualification, 'chi-squared test' often is used as short for Pearson's chi-squared test.
Chi-Square Tests tribution is based are squared, so that the symbol ´2 is used to denote the distribution. An example of the chi squared distribution is given in Figure Minitab also can help you prepare your data for analysis.
For example, one of your survey questions asked people to rank a product on a 7-point scale, and you want to classify responses 6 and 7 as positive, 3 to 5 as neutral, and 1 and 2 as negative.