SPSS Survey Analysis & Interpretation Expert

Hiring: SPSS Expert — clean, analyse and interpret survey (ready-to-run deliverables). I need an SPSS expert to take my raw Excel survey (n≈160+) and deliver a fully reproducible analysis and concise interpretations I can paste into a report; tone must be professional, concise, no hand-holding. The analysis pipeline must follow the sequence: (1) Descriptive statistics — full univariate reporting (frequencies for demographics and yes/no items; descriptives mean ± SD, min, max for all Likert/numeric items; Multiple-Response sets for all “select all that apply” questions with option frequencies/percentages; flag extreme skew/low variance/missingness and recommend remedies); (2) Cross-tabulations / bivariate analysis — produce requested crosstabs with Chi-square, row/column/total % and cell counts for Religion × Awareness_of_Halal, Gender × Bought_last12m, Age × Heard_of_Duopharma, and test Seen_Ads_60d × Impression_score using t-test/ANOVA (with Levene’s) or non-parametric alternatives as appropriate; explicitly flag expected cell counts <5 and recommend/implement remedies (collapse categories or Fisher’s exact) with justification; (3) Scale reliability & composite scores — run Cronbach’s α on the six halal perception items (Safe, Effective, Hygienic, High_quality, Ethical, Permissible), report item-total correlations and α-if-item-deleted, and if α≥0.70 compute halal_perception composite (document whether mean or sum), output descriptives and distribution; if α<0.70 provide concrete recommendations (which item(s) to drop or to treat separately) grounded in diagnostics and theory; (4) Regression analysis — recode the purchase intent question into binary purchase_intent (top-2 → 1; others → 0) and show frequencies, check multicollinearity (VIF/Tolerance, condition indices) and remediate if needed, then run a binary logistic regression predicting purchase_intent using the final model: halal_perception, Importance_Halal_cert, Importance_Halal_logo, Aware_Halal_JAKIM, Heard_of_Duopharma, Confidence_Duopharma_Halal, Seen_Ads_60d, Bought_last12m, freq_buy plus controls (Age, Gender, Household_income); report −2LL, Model χ² (df, p), Nagelkerke R², Hosmer-Lemeshow, classification table (sensitivity/specificity/overall accuracy), and odds ratios with 95% CIs and p-values, note any sample-size/events-per-variable issues and propose a principled reduced model if needed. Deliverables (reproducible, ready to paste): 1) Data preparation: cleaned original file and cleaned .sav; missing values fixed/marked, miscoding corrected (e.g., 99→system-missing), variable names standardised (no spaces), value labels, Measure (Nominal/Ordinal/Scale) and readable variable labels added in Variable View; 2) SPSS syntax file (.sps) fully commented so one click reruns everything; 3) Output tables (Word or PDF): Demographics table, Item descriptives, Multiple-Response frequencies, Cronbach’s alpha table and reliability diagnostics, requested crosstabs with chi-square and notes on low cell counts, full logistic regression table and diagnostics; 4) Charts as PNGs (2–3 useful plots: e.g., brand awareness bar, histogram of halal_perception composite, forest plot of ORs); 5) Short interpretive memo (max 1 page): 3–5 key findings, implications for purchase behaviour, and 3 tactical evidence-linked recommendations to raise purchase intention; 6) Data dictionary / codebook listing variable names, labels and value labels. Diagnostics & robustness: provide VIF table and any remedial steps taken (category collapse, variable removal), influence diagnostics, assessment of linearity in the logit for continuous predictors, and optional subgroup analysis (e.g., Muslims vs non-Muslims) if materially different — state if performed. Confidentiality: confirm data will not be shared and will be deleted on request. Required skills & tools: expert in SPSS (syntax + GUI; compatibility with .sav and Excel import), strong survey analysis experience (MR sets, reliability, chi-square, t-test/ANOVA, non-parametric tests, logistic regression, diagnostics), and clear written English able to produce concise interpretation for non-technical stakeholders. Timeline: indicate earliest start date and estimated turnaround; include fixed price for the full scope and note willingness to provide a short sample output (e.g., one crosstab and one chart) on a single test variable if required. To apply send a brief statement of relevant experience, confirmation you will deliver the exact files listed above, and one line confirming confidentiality.