SPSS Report on Religiosity and Spirituality in Romantic Relationship

SPSS Lab Report
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SPSS LAB Report
Introduction
This SPSS report shall conduct the basic SPSS procedures based on the dataset attached. The data was compiled based on the questionnaire section of Topic 6 material of Religiosity and Spirituality in Romantic Relationship Questionnaire. Based on the dataset attached, the steps involved were cleaning data, data input, obtaining the central data tendency, different measures combination, and testing of hypothesis. The data is in a readable excel SPSS format entered in the SPSS data sheet. In the column, inserted unique variable names respectively.
Step 1: Clean your data.
Then, inserted descriptive text variables racial-ethnic background, school area, romantic relationship, gender, the impact of spiritual belief on the romantic relationship, and age. The youth attending religious amenities with both or one of their parents are highly likely to feel better well-being with their loving partners who pray for their experience significant others greater committed relationship. From the data, Religion is characterized by belief systems shared by institutional and community contexts expressed in shared behaviors and values.
Demographic Variable of Religion Analysis
In the selected data, the critical demographic variable is Religion from the survey data as a component of the demographic variable like age, gender, ethnicity, race, income, or education. The values represent the sample providing valuable analysis describing the participants to aid the research. A measure of Religion is of particular interest to social scientists in understanding the participants' lifestyles, attitudes, beliefs, and behaviors. In addition, the researcher aims to identify the relationship between Religion and the outcome of a romantic relationship. Therefore, Religion is a ratio continuous demographic variable.
Figure 1: Linkert Scale Religious values/beliefs effect on romantic relationship(s).
The variable View indicates the various variable components, including Measure, Values, Label, and Name, with the last variable showing the vital element. For example, the SPSS variable can be 64 extended characters. The Measure column indicates the Nominal variable with no intrinsic values like ethnicity and gender.
Step 2: Describe your Data
The three variables were based on the Frequent, Descriptive Statistics 5and Data analysis in calculating the right central tendencies...