Question

(using program sps modeler IBM)Use the data regulation charges to answer the following questions. The data were collected within a questionnaire survey focusing on opinions towards new regulation charges for health care services in the Czech Republic.

What are the absolute frequency and proportion of male respondents?
What is the minimal, maximal, and mean age of all respondents?
What is the proportion of female respondents with a college degree?
How many men answered they „somewhat agree" with regulation charges? Put down the absolute frequency and the percentage (out of all men).
What is the minimal, maximal, and mean age of respondents who „totally agree" with regulation charges?
What is the proportion of women who answered that they „totally disagree" with regulation charges (out of all women)?
Create a new binary variable (agree/disagree) based on the categorical variable evaluation_charges by merging categories totally agree + somewhat agree (agree) and totally disagree + somewhat disagree (disagree). What is the number of respondents who disagreed with regulation charges? Put down also the percentage.
Create a new categorical variable, „age categories, " as follows:
20 to 35 years
36 to 55 years
56 and older.
What is the proportion of respondents within the age category of the highest frequency?
Create a new categorical variable based on the respondent’s age so that each category represents approx. 25% of all observations.
What is the interval range of the youngest age category?

Answer 1

Survey data analysis involves calculating frequencies, proportions, and measures of central tendency, and often requires creating new variables for analysis. Techniques like hypothesis testing are used to determine sample representativeness or analyze distributions among different groups.

Step-by-step explanation:

Understanding Survey Data Analysis

To analyze the survey data from the Czech Republic healthcare regulation charges questionnaire, you would typically apply statistical techniques. Describing the frequency and proportion of characteristics like gender or opinions among respondents is essential. Calculating measures of central tendency such as mean age and establishing new variables for analytical convenience is also common practice. For example, creating a binary variable for agreement level with regulation charges helps to simplify the analysis.

Analyzing the composition of respondents concerning education levels and attitudes towards policy is a fundamental aspect of sociological research. To perform these tasks in IBM SPSS Modeler, you would need the raw data from the survey, which would include variables such as age, gender, education level, and opinions on regulation charges.

Regarding drawing conclusions about the representative nature of a survey sample or analyzing the distribution of living arrangements among college students, you would apply hypothesis testing techniques. Similarly, the marketing manager, the librarian, or the political party would use inferential statistics to generalize their findings to a broader population when examining ages, patron demographics, or voter reactions, respectively.