ܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ: ܦܘܠ̈ܓܐ ܕܥܡܘ̈ܕܐ – ܠܘ̈ܚܐ ܠܦܘܬ ܓܘ̈ܕܐ

1. ܛܥܢܐ ܕܝܗܝ̈ܒܬܐ

ܟܡܕܒܩܚ ܥܡܘ̈ܕܐ ܬܪܝܨܐܝܬ ܡܢ ܓܠܝܘܢܐ (worksheet)، ܥܡ ܣܕܪܐ ܕܪ̈ܫܐ (header row) – ܟܪܫܡܚ ܓܘ ܐܩܣܠ، ܟܢܣܚܚ، ܘܟܡܕܒܩܚ ܠܐܟܐ:

ܐܝܡܢ ܡܦܠܚܝܚ (When to use)؟

ܒܬܪ ܕܡܘܕܥܢܘܬܐ ܕܠܘ̈ܚܐ ܕ-ܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܦܢܝܠܗ ܥܠ "ܟܡܐ؟"، ܦܘܠܓܐ ܕܥܡܘ̈ܕܐ ܟܦܢܐ ܥܠ "ܓܘ ܡܢܘ؟": ܐܢ ܒܣܝܡܘܬܐ ܦܪܝܫܬܐ ܝܠܗ ܒܝܢܝ ܓܒܪ̈ܐ ܘܢܫ̈ܐ، ܒܝܢܝ ܓܘ̈ܕܐ ܕܥܘܡܪܐ، ܒܝܢܝ ܦܢܝ̈ܬܐ ܕܥܡܪܐ. ܓܘ ܒܝ̈ܬܐ ܕܒܘܨܝܐ ܐܗܐ ܝܠܗ "ܡܘܕܥܢܘܬܐ ܕܦܘܠ̈ܓܐ" – ܗܢ ܫܘܐ̈ܠܐ، ܗܢ ܣܕܪ̈ܐ، ܐܝܢܐ ܒܕܘܟܬܐ ܕܚܕ ܥܡܘܕܐ ܕܓܘܡܪܐ ܐܝܬ ܥܡܘܕܐ ܩܐ ܟܠ ܓܘܕܐ ܙܥܘܪܬܐ (banner، ܪ̈ܫܐ ܕܥܡܘ̈ܕܐ). ܓܘ ܣܩܪ̈ܝܦܬܐ ܥܬܝܩ̈ܐ ܐܗܐ ܝܠܗ ܗܘܐ /TABLE= q + $t000001 BY kk: kk ܝܠܗ ܡܫܬܚܠܦܢܐ ܕܪ̈ܫܐ ܕܥܡܘ̈ܕܐ، cpct – ܡܢܬܐ ܒܡܐܐ ܕܥܡܘܕܐ، count 'N' – ܣܕܪܐ ܕܫܬܐܣܐ. ܐܗܐ ܦܐܬܐ ܚܬܝܬܐܝܬ ܟܒܢܐ ܐܗܐ ܠܘܚܐ، ܘܟܡܘܣܦܐ ܡܐ ܕܣܩܪ̈ܝܦܬܐ ܠܐ ܥܒܕܠܗܘܢ: ܒܘܚܪܢܐ ܕܟܝ ܡܪܒܥܐ ܩܐ ܟܠ ܫܘܐܠܐ × ܡܫܬܚܠܦܢܐ ܕܬܚܘܝܬܐ، V ܕ-Cramér ܘܪܘܫܡܐ ܕܩܠ̈ܝܬܐ ܕܟܦܪܫܝ ܡܢ ܡܣܟܝܐ.

ܐܗܐ ܦܐܬܐ ܦܐܫ ܠܟܠ ܫܘܐܠܐ ܣܟܝܪܐ ܕܐܝܬ ܠܗ ܓܘ̈ܕܐ ܩܐ ܦܘܚܡܐ: ܦܘܢܝܐ ܝܚܝܕܝܐ (ܠܘܚܐ ܪܓܝܠܐ)، ܦܘܢ̈ܝܐ ܣܓܝ̈ܐܐ (ܡܢܬܐ ܒܡܐܐ ܡܢ ܡܦܢܝ̈ܢܐ ܓܘ ܟܠ ܓܘܕܐ)، ܣܕܪܐ ܕܫܘܐ̈ܠܐ (battery؛ ܡܨܥܝܬܐ ܩܐ ܦܣܘܩܐ ܓܘ ܟܠ ܓܘܕܐ) ܘܡܫܬܚܠܦܢܐ ܡܬܡܫܚܢܐ (ܡܨܥܝܬܐ، SD ܘܛܝܡܐ ܡܨܥܝܐ ܓܘ ܟܠ ܓܘܕܐ). ܡܐ ܕܠܐ ܟܥܒܕ – ܕܡܦܫܩ ܩܐ ܡܘܕܝ ܓܘ̈ܕܐ ܦܪ̈ܝܫܐ ܝܢܐ؛ ܩܐ ܐܗܐ ܣܢܝܩ ܝܠܗ ܡܘܕܝܠ (ܚܙܝܡܘܢ ܛܥܝ̈ܘܬܐ ܕܡܬܚܙܝܢ ܣܓܝ).

ܐܘܪܚܐ ܕܥܒܕܐ – ܡܢ ܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܠܦܘܠ̈ܓܐ ܕܥܡܘ̈ܕܐ

1. ܟܫܪܝܚ ܓܘ ܦܐܬܐ ܕܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ. ܬܡܢ ܟܒܢܝܚ ܟܬܒܐ ܕܪ̈ܡܙܐ (codebook)، ܟܒܚܪܚ ܝܗܝ̈ܒܬܐ، ܟܪܡܙܚ ܡܢ ܪܝܫ (ܓܘ̈ܕܐ ܕܥܘܡܪܐ – ܪܫܐ ܕܥܡܘ̈ܕܐ ܠܐ ܡܨܝܚ ܕܒܢܝܚ ܡܢ ܥܘܡܪܐ ܡܬܡܫܚܢܐ)، ܟܨܠܠܚ ܘܟܬܩܠܚ – ܘܟܡܚܬܚ "ܦܐܝܠ ܥܡ ܟܬܒܐ ܕܪ̈ܡܙܐ ܚܕܬܐ". ܓܠܝܘܢܐ ܕܬܘܩ̈ܢܐ (settings / הגדרות) ܕܓܘܗ ܟܢܛܪ ܟܠ ܡܕܡ.
2. ܟܛܥܢܚ ܐܗܐ ܦܐܝܠ ܠܐܟܐ. ܟܬܒܐ ܕܪ̈ܡܙܐ، ܪܡܙܢܘܬܐ، ܡܨܠܠܢܘܬܐ، ܡܬܩܠܢܘܬܐ ܘܫܬܐܣܐ ܕܡܢܘ̈ܬܐ ܒܡܐܐ ܟܡܬܛܥܢܝ ܡܢ ܓܢܗܘܢ (ܡܘܕܥܢܘܬܐ "ܬܘܩ̈ܢܐ ܢܛܝܪ̈ܐ ܝܢܐ ܓܘ ܦܐܝܠ"). ܡܨܝܚ ܐܦ ܕܛܥܢܚ ܦܐܝܠ ܪܓܝܠܐ ܥܡ ܡܦܫܩܢܐ (legend) ܘܟܬܒܚ ܡܛܝܒܘܬܐ ܓܘ ܦܣܩܐ 3، ܝܢ "ܛܥܢܐ ܕܬܘܩ̈ܢܐ ܡܢ ܦܐܝܠ" (settings.json ܡܢ ܨܪܪܐ ܕܒܘܨܝܐ).
3. ܟܓܒܚ ܪ̈ܫܐ ܕܥܡܘ̈ܕܐ (ܦܣܩܐ 4) – ܐܝܟ ܓܘܒܝܐ ܡܩܕܡܐ ܡܫܬܚܠܦ̈ܢܐ ܕܬܚܘܝܬܐ، ܥܡ ܡܦܩ̈ܐ ܐܝܟ ܓܘܕܐ ܕܥܘܡܪܐ.
4. ܟܒܢܝܚ. ܠܘܚܐ 1 ܪܒܘܬܐ ܕܟܠ ܓܘܕܐ ܝܠܗ (ܩܐ ܕܚܙܝܚ ܡܢ ܩܕܡ ܥܡܘ̈ܕܐ ܙܥܘܪ̈ܐ)؛ ܒܬܪܗ ܠܘܚܐ ܩܐ ܟܠ ܫܘܐܠܐ؛ ܓܘ ܣܘܦܐ – ܠܘܚܐ ܕܟܢܘܫܝܐ ܕܒܘܚܪ̈ܢܐ، ܡܐܡܪ̈ܐ ܕܬܘܢܝܐ (report sentences) ܘܩܪܝܢܐ ܕܦܐܪܐ.
5. ܟܡܚܬܚ Word ܝܢ HTML، ܘܣܝܢܬܐܟܣ (SPSS) ܝܢ ܣܩܪܝܦܬ (R) ܕܟܬܢܝ ܡܢܝ̈ܢܐ. ܬܘܩ̈ܢܐ ܕܐܗܐ ܦܐܬܐ (ܪ̈ܫܐ ܕܥܡܘ̈ܕܐ ܘܓܘܒܝ̈ܐ) ܟܡܬܢܛܪܝ ܓܘ ܦܐܝܠ ܕܟܢܚܬ ܡܢ "ܡܚܬܬܐ ܕܦܐܝܠ ܥܡ ܟܬܒܐ ܕܪ̈ܡܙܐ ܘܬܘܩ̈ܢܐ" – ܟܛܥܢܚ ܠܗ ܬܘܒ ܘܡܘܕܥܢܘܬܐ ܟܡܬܢܝܐ.

ܪ̈ܫܐ ܕܥܡܘ̈ܕܐ – ܡܘܕܝ ܟܥܒܕ ܡܫܬܚܠܦܢܐ ܠܥܡܘ̈ܕܐ ܛܒ̈ܐ؟

ܓܢ̈ܣܐ ܩܠܝܠ̈ܐ، ܡܦܢܝ̈ܢܐ ܣܓܝ̈ܐܐ ܓܘ ܟܠ ܚܕ. ܐܗܐ ܦܐܬܐ ܟܡܩܪܒ ܡܫܬܚܠܦ̈ܢܐ ܕܓܢ̈ܣܐ (categorical) ܝܢ ܡܫܬܚܠܦ̈ܢܐ ܕܛܟܣܐ (ordinal) ܥܡ 2-12 ܓܢ̈ܣܐ. ܥܘܡܪܐ، ܐܓܪܐ ܝܢ ܥܬܝܩܘܬܐ ܡܬܡܫܚ̈ܢܐ ܠܐ ܡܬܩܪ̈ܒܐ ܝܢܐ – ܟܟܢܫܚ ܠܗܘܢ ܩܕܡ ܒܪܡܙܢܘܬܐ ܡܢ ܪܝܫ (Section 3; Pallant, 2020, Chapter 8 – Recode into Different Variables)، ܘܡܫܬܚܠܦܢܐ ܡܦܩܐ ܟܥܐܠ ܡܢ ܓܢܗ ܠܪܫܝܡܬܐ. ܢܡܘܣܐ ܕܥܒܕܐ ܕܒܝ̈ܬܐ ܕܒܘܨܝܐ: ܥܡܘܕܐ ܥܡ ܒܨܝܪ ܡܢ 30 ܡܦܢܝ̈ܢܐ ܡܬܬܢܝܐ ܒܙܗܝܪܘܬܐ – ܡܢܬܐ ܒܡܐܐ ܥܠ 20 ܐܢܫ̈ܐ ܟܙܝܥ 5 ܢܘܩ̈ܙܐ ܥܡ ܟܠ ܡܦܢܝܢܐ. ܠܘܚܐ 1 ܟܡܚܘܐ ܪܒܘܬܐ ܕܟܠ ܓܘܕܐ ܩܕܡ ܕܩܪܚ ܠܘ̈ܚܐ، ܘܟܠ ܡܥܝܪܢܘܬܐ ܕܠܘܚܐ ܟܡܚܘܝܐ ܥܡܘ̈ܕܐ ܙܥܘܪ̈ܐ.

ܡܢܘ ܠܐ ܝܠܗ ܓܘ ܥܡܘ̈ܕܐ. ܡܦܢܝܢܐ ܕܠܐ ܦܢܐ ܥܠ ܫܘܐܠܐ ܕܬܚܘܝܬܐ (ܣܦܝܩܐ)، ܝܢ ܦܢܐ "ܠܐ ܝܕܥܢ/ܠܐ ܨܒܐ ܠܡܦܢܝܐ" (ܪܡܙܐ ܕܪܫܝܡܐ ܝܠܗ ܓܘ ܟܬܒܐ ܕܪ̈ܡܙܐ ܐܝܟ ܠܐ ܦܘܢܝܐ ܕܒܥܠ ܣܘܟܠܐ)، ܠܐ ܝܠܗ ܕܚܕܐ ܓܘܕܐ – ܐܝܢܐ ܥܠܝܠܐ ܝܠܗ ܓܘ ܥܡܘܕܐ ܕܓܘܡܪܐ ܘܠܐ ܓܘ ܥܡܘ̈ܕܐ. ܛܝܡܐ ܕܠܐ ܝܠܗ ܓܘ ܪܫܝܡܬܐ ܕܪ̈ܡܙܐ (ܡܬܠܐ 3 ܓܘ ܡܫܬܚܠܦܢܐ ܕܓܢܣܐ ܕܪܡܝܙܐ ܝܠܗ 1/2) ܩܪܝܒܐܝܬ ܟܠ ܙܒܢܐ ܛܥܝܘܬܐ ܕܡܥܠܬܐ ܝܠܗ: ܐܝܟ ܓܘܒܝܐ ܡܩܕܡܐ ܐܦ ܐܝܢܐ ܟܦܐܫ ܓܘ ܓܘܡܪܐ ܒܣ ܘܪܫܝܡܐ ܝܠܗ ܒܨܒܥܐ ܣܘܡܩܐ ܓܘ ܠܘܚܐ 1 ܘܓܘ ܩܪܝܢܐ ܕܦܐܪܐ؛ ܐܝܢܐ ܕܒܥܐ ܕܚܙܐ ܠܗ ܐܝܟ ܥܡܘܕܐ (ܐܝܟ ܕ-SPSS ܟܥܒܕ) ܟܪܫܡ "ܥܡܘܕܐ ܐܦ ܩܐ ܛܝܡܐ ܕܠܐ ܝܠܗ ܓܘ ܟܬܒܐ ܕܪ̈ܡܙܐ". ܐܗܐ ܟܡܫܚܠܦ ܐܦ ܒܘܚܪܢܐ: ܥܡܘܕܐ ܕܚܕ ܡܦܢܝܢܐ ܟܡܘܣܦܐ ܣܕܪܐ ܕܕܪ̈ܓܐ ܕܚܐܪܘܬܐ ܘܩܠ̈ܝܬܐ ܡܣܟ̈ܝܬܐ ܕܨܦܪܐ.

ܬܚܘܝܬܐ × ܬܚܘܝܬܐ. ܐܝܟ ܓܘܒܝܐ ܡܩܕܡܐ ܐܦ ܡܫܬܚܠܦ̈ܢܐ ܕܬܚܘܝܬܐ ܡܬܦܠܓ̈ܐ ܝܢܐ ܚܕ ܠܦܘܬ ܐܚܪܢܐ (ܓܢܣܐ ܠܦܘܬ ܓܘܕܐ ܕܥܘܡܪܐ، ܝܘܠܦܢܐ ܠܦܘܬ ܦܢܝܬܐ) – ܐܢܝ ܠܘ̈ܚܐ ܒܥܕܢ̈ܐ ܣܓܝ̈ܐܐ ܟܡܦܫܩܝ ܡܫܟܚܢܘܬܐ "ܠܦܘܬ ܥܘܡܪܐ" ܕܒܥܒܕܐ "ܠܦܘܬ ܝܘܠܦܢܐ" ܝܠܗ. ܡܫܬܚܠܦܢܐ ܠܐ ܡܬܦܠܓ ܠܦܘܬ ܓܢܗ.

ܩܪܝܢܐ ܕܠܘܚܐ؟

ܟܠ ܩܠܝܬܐ ܡܢܬܐ ܒܡܐܐ ܕܥܡܘܕܐ ܝܠܗ: ܡܢ ܡܦܢܝ̈ܢܐ ܕܓܘ ܥܡܘܕܐ، ܟܡܐ ܓܒܠܗܘܢ ܦܘܢܝܐ ܕܓܘ ܣܕܪܐ. ܥܡܘ̈ܕܐ ܟܡܛܝܝ ܠ-100 (ܣܕܪܐ ܕ"ܓܘܡܪܐ")؛ ܦܘܚܡܐ ܠܦܬܝܘܬܐ ܝܠܗ – ܒܝܢܝ ܥܡܘ̈ܕܐ، ܘܩܘܒܠ ܥܡܘܕܐ ܕܓܘܡܪܐ. ܐܝܢܐ ܕܒܥܐ ܕܝܕܥ ܐܦ ܟܡܐ ܐܢܫ̈ܐ ܩܝܡ̈ܐ ܝܢܐ ܒܬܪ ܡܢܬܐ ܒܡܐܐ ܟܓܒܐ "ܡܢܬܐ ܒܡܐܐ ܘ-n ܓܘ ܩܘܠܦ̈ܐ"؛ ܒܟܠ ܓܒܐ ܣܕܪܐ ܕ-n ܓܘ ܬܚܬܝܬܐ ܟܝܗܒ ܫܬܐܣܐ (base) ܕܟܠ ܥܡܘܕܐ – ܡܢܝܢܐ ܕܡܦܢܝ̈ܢܐ ܥܡ ܦܘܢܝܐ ܕܒܥܠ ܣܘܟܠܐ (ܓܘ ܫܬܐܣܐ ܕܓܘܒܝܐ ܡܩܕܡܐ) ܓܘ ܓܘܕܐ. ܓܘ ܡܘܕܥܢܘܬܐ ܡܬܩܠܬܐ ܟܡܬܘܣܦܐ ܣܕܪܐ ܕ"ܫܬܐܣܐ ܡܬܩܠܐ".

ܥܡܘܕܐ ܕܓܘܡܪܐ ܠܘܚܐ ܝܠܗ ܡܢ ܦܐܬܐ ܕܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ – ܟܠ ܡܦܢܝ̈ܢܐ، ܥܡ ܐܢܝ ܕܠܐ ܝܢܐ ܓܘ ܚܕ ܥܡܘܕܐ (ܣܦܝܩܐ ܝܢ "ܠܐ ܨܒܐ ܠܡܦܢܝܐ" ܓܘ ܫܘܐܠܐ ܕܬܚܘܝܬܐ). ܡܛܠ ܗܕܐ ܓܘܡܪܐ ܕ-n ܕܥܡܘ̈ܕܐ ܡܨܐ ܕܗܘܐ ܙܥܘܪܐ ܡܢ n ܕܓܘܡܪܐ؛ ܡܥܝܪܢܘܬܐ ܕܠܘܚܐ ܟܐܡܪܐ ܒܟܡܐ. (ܓܘ SPSS، CROSSTABS ܟܡܚܘܐ Total ܒܣ ܩܐ ܐܝܢܐ ܕܐܝܬ ܠܗ ܛܝܡܐ ܓܘ ܬܪܘܝܗܝ ܡܫܬܚܠܦ̈ܢܐ – ܚܙܝܡܘܢ ܠܬܚܬ.)

ܫܬܐܣܐ ܗܘ ܫܬܐܣܐ ܝܠܗ ܐܝܟ ܓܘ ܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ – "ܡܦܢܝ̈ܢܐ ܥܡ ܦܘܢܝܐ ܕܒܥܠ ܣܘܟܠܐ" ܐܝܟ ܓܘܒܝܐ ܡܩܕܡܐ: "ܠܐ ܝܕܥܢ" ܘܣܦܝܩ̈ܐ ܠܒܪ ܡܢ ܡܢܘ̈ܬܐ ܒܡܐܐ ܝܢܐ ܘܡܬܬܢܝ̈ܐ ܝܢܐ ܓܘ ܡܥܝܪܢܘܬܐ؛ "ܟܠ ܡܢ ܕܦܢܐ" ܟܡܥܠܐ "ܠܐ ܝܕܥܢ" ܐܝܟ ܣܕܪܐ؛ "ܟܠ ܡܦܢܝ̈ܢܐ" ܟܡܘܣܦܐ ܣܕܪܐ ܕ"ܠܐ ܦܢܐ/ܦܢܝܐ". ܫܘܐܠܐ ܕܡܫܐܠܐ ܝܠܗ ܒܣ ܡܢ ܡܢܬܐ ܡܢ ܡܦܢܝ̈ܢܐ ("ܡܫܐܠܐ ܐܢ") ܚܫܝܒܐ ܝܠܗ ܥܠ ܫܘ̈ܝܐ ܓܘ ܟܠ ܥܡܘܕܐ. ܬܠܬܐ ܡܕܡ̈ܐ ܩܐ ܚܙܝܐ ܩܕܡ ܕܡܬܚܚ: ܣܕܪ̈ܐ ܥܡ 0 ܓܘ ܟܠ ܥܡܘ̈ܕܐ (ܓܢܣܐ ܕܚܕ ܠܐ ܓܒܠܗ – ܡܚܘܝܐ ܝܠܗ ܐܝܟ ܓܘܒܝܐ ܡܩܕܡܐ، ܡܨܝܚ ܕܛܫܚ ܠܗ)، ܥܡܘܕܐ ܕܠܐ ܪܘܫܡܐ (ܛܝܡܐ ܕܠܐ ܝܠܗ ܓܘ ܟܬܒܐ ܕܪ̈ܡܙܐ)، ܘܫܬܐܣܐ ܙܥܘܪܐ.

ܒܘܚܪܢܐ: ܟܝ ܡܪܒܥܐ ܠܠܐ ܬܠܝܘܬܐ ܘ-V ܕ-Cramér

ܩܐ ܟܠ ܫܘܐܠܐ × ܡܫܬܚܠܦܢܐ ܕܬܚܘܝܬܐ ܐܗܐ ܦܐܬܐ ܟܪܗܛ ܒܘܚܪܢܐ ܕܟܝ ܡܪܒܥܐ ܠܠܐ ܬܠܝܘܬܐ ܕ-Pearson (Field, 2024, Section 19.3; Pallant, 2020, Chapter 16): ܐܢ ܦܘܠܓܐ (distribution) ܕܦܘܢ̈ܝܐ ܦܪܝܫܐ ܝܠܗ ܒܝܢܝ ܥܡܘ̈ܕܐ، ܝܢ ܦܘܪ̈ܫܢܐ ܕܟܡܬܚܙܝ ܓܘ ܠܘܚܐ ܐܢܝ ܝܢܐ ܕܡܣܟ̈ܝܐ ܝܢܐ ܓܘ ܕܘܡܝܐ ܓܕܫܢܝܐ ܐܡܬܝ ܕܠܝܬ ܐܣܘܪܐ. ܣܓܝܐܘܬܐ ܡܣܟܝܬܐ ܓܘ ܟܠ ܩܠܝܬܐ ܟܐܬܝܐ ܡܢ ܣܦܪ̈ܐ ܕܠܘܚܐ ܒܣ، ܘܡܢܝܢܐ ܣܛܐܛܝܣܛܝܩܝܐ ܟܟܢܫ ܦܘܪ̈ܫܢܐ ܒܝܢܝ ܚܙܝܐ ܘܡܣܟܝܐ. ܒܘܚܪܢܐ ܟܪܗܛ ܥܠ ܡܢܝ̈ܢܐ ܕܦܘܢ̈ܝܐ ܕܒܥܠ ܣܘܟܠܐ ܒܣ – ܕܠܐ "ܠܐ ܝܕܥܢ"، ܕܠܐ ܣܦܝܩ̈ܐ – ܘܣܕܪܐ ܝܢ ܥܡܘܕܐ ܣܦܝܩ̈ܐ ܫܩܝܠ̈ܐ ܝܢܐ ܡܢܗ (ܐܝܟ ܓܘ SPSS، ܕܓܘܗ ܓܢܣܐ ܕܠܐ ܓܒ̈ܐ ܠܐ ܝܠܗ ܓܘ ܠܘܚܐ). ܣܕܪܐ ܕܒܘܚܪܢܐ ܓܘ ܡܥܝܪܢܘܬܐ ܕܟܠ ܠܘܚܐ: χ²(df, N) = …, p = …, V ܕ-Cramér = …، ܘܠܘܚܐ ܕܟܢܘܫܝܐ ܓܘ ܣܘܦܐ ܕܡܘܕܥܢܘܬܐ ܟܟܢܫ ܠܟܠܗܘܢ.

ܫܪܛܐ. ܒܘܚܪܢܐ ܩܘܪܒܢܝܐ ܝܠܗ، ܘܩܘܪܒܐ ܛܒܐ ܝܠܗ ܐܡܬܝ ܕܣܓܝܐܘ̈ܬܐ ܡܣܟ̈ܝܬܐ ܠܐ ܝܢܐ ܙܥܘܪ̈ܐ ܣܓܝ: ܓܘ ܠܘܚܐ 2×2 ܚܕܐ ܩܠܝܬܐ ܡܣܟܝܬܐ ܠܐ ܠܬܚܬ ܡܢ 5؛ ܓܘ ܠܘܚܐ ܪܒܐ ܝܬܝܪ – ܟܠ ܩܠ̈ܝܬܐ ܠܥܠ ܡܢ 1 ܘܠܐ ܝܬܝܪ ܡܢ 20% ܠܬܚܬ ܡܢ 5 (Field, 2024, Section 19.5.2). ܐܡܬܝ ܕܫܪܛܐ ܥܒܝܪܐ ܝܠܗ ܐܗܐ ܦܐܬܐ ܟܟܬܒ ܐܗܐ ܓܘ ܡܥܝܪܢܘܬܐ ("ܒܘܚܪܢܐ ܩܘܪܒܢܝܐ ܝܠܗ") ܘܓܘ ܠܘܚܐ ܕܟܢܘܫܝܐ؛ ܦܘܫܪܐ ܪܓܝܠܐ ܓܘ ܦܘܠ̈ܓܐ ܕܥܡܘ̈ܕܐ ܚܘܝܕܐ ܕܓܢ̈ܣܐ ܝܠܗ (ܣܕܪ̈ܐ ܝܢ ܥܡܘ̈ܕܐ) ܒܪܡܙܢܘܬܐ ܡܢ ܪܝܫ. ܓܘ ܠܘܚܐ 2×2 ܙܥܘܪܐ ܟܡܬܢܚ ܒܘܚܪܢܐ ܚܬܝܬܐ ܕ-Fisher – ܓܘ ܦܐܬܐ ܕܟܝ ܡܪܒܥܐ.

ܚܝܠܐ، ܠܐ ܪܫܝܡܘܬܐ ܒܣ. ܓܘ ܕܘܡܝܐ ܪܒܐ ܐܦ ܦܘܪܫܢܐ ܕܩܠܝܠ ܢܘܩ̈ܙܐ ܕܡܢܬܐ ܒܡܐܐ ܟܗܘܐ ܪܫܝܡܐ؛ ܪܫܝܡܘܬܐ (significance) ܟܐܡܪܐ ܕܐܝܬ ܐܣܘܪܐ، ܠܐ ܟܡܐ ܚܝܠܢܐ ܝܠܗ (Field, 2024, Section 19.5.3). V ܕ-Cramér – √(χ²/(N·df*))، df* = min(r − 1, c − 1) (Gravetter & Wallnau, 2017, Equation 17.9) – ܝܠܗ ܒܝܢܝ 0 ܘ-1 ܘܠܐ ܝܠܗ ܬܠܝܐ ܒܪܒܘܬܐ ܕܕܘܡܝܐ. ܬܚܘ̈ܡܐ ܕ-Cohen ܩܐ ܪܒܘܬܐ ܕܡܥܒܕܢܘܬܐ (effect size): .10 ܙܥܘܪܐ، .30 ܡܨܥܝܐ، .50 ܪܒܐ (Cohen, 1988، ܐܝܟ ܕܡܬܡܠܠ ܓܘ Pallant, 2020، ܘܓܘ Gravetter & Wallnau, 2017) – ܘܠܘܚܐ ܪܒܐ ܝܬܝܪ ܬܚܘ̈ܡܐ ܩܐ V ܢܚ̈ܝܬܐ ܝܢܐ ܝܬܝܪ، ܠܦܘܬ df* (Gravetter & Wallnau, Table 17.10)؛ ܐܗܐ ܦܐܬܐ ܟܡܦܩ: "ܡܥܒܕܢܘܬܐ ܙܥܘܪܬܐ/ܡܨܥܝܬܐ/ܪܒܬܐ" ܓܘ ܡܥܝܪܢܘܬܐ ܘܓܘ ܡܐܡܪܐ ܕܬܘܢܝܐ ܠܦܘܬ w = V·√df*، ܐܝܟ ܓܘ ܦܐܬܐ ܕܟܝ ܡܪܒܥܐ.

ܒܘܚܪ̈ܢܐ ܣܓܝ̈ܐܐ. ܡܘܕܥܢܘܬܐ ܪܓܝܠܬܐ ܕܦܘܠ̈ܓܐ ܕܥܡܘ̈ܕܐ ܟܪܗܛܐ ܥܣܪ̈ܐ ܕܒܘܚܪ̈ܢܐ (ܫܘܐ̈ܠܐ × ܡܫܬܚܠܦ̈ܢܐ ܕܬܚܘܝܬܐ)، ܘܓܘ ܟܠ 20 ܒܘܚܪ̈ܢܐ ܚܕ ܡܣܟܝܐ ܝܠܗ ܕܗܘܐ ܪܫܝܡܐ ܒܓܕܫܐ ܐܦ ܐܡܬܝ ܕܠܝܬ ܚܕ ܐܣܘܪܐ. ܡܛܠ ܗܕܐ ܐܗܐ ܦܐܬܐ ܟܬܢܐ ܟܡܐ ܒܘܚܪ̈ܢܐ ܪܗܛ̈ܐ ܝܢܐ ܘܟܡܐ ܗܘܘ ܪܫܝܡ̈ܐ، ܘܟܡܥܗܕ ܐܗܐ ܓܘ ܩܪܝܢܐ ܕܦܐܪܐ. ܦܘܫܩܐ ܬܪܝܨܐ ܛܘܦܣܐ ܝܠܗ: ܐܣܘܪܐ ܕܟܕܥܪ ܓܘ ܟܡܐ ܫܘܐ̈ܠܐ ܩܪܝܒ̈ܐ، ܥܡ V ܕܠܐ ܝܠܗ ܙܥܘܪܐ ܛܒܐ – ܘܠܐ ܦܘܚܡܐ ܝܚܝܕܝܐ ܕܥܒܪܠܗ .05. ܐܝܢܐ ܕܣܢܝܩ ܝܠܗ ܠܬܚܘܡܐ ܡܬܘܪܨܐ ܟܡܦܠܓ .05 ܥܠ ܡܢܝܢܐ ܕܒܘܚܪ̈ܢܐ (Bonferroni) ܘܟܪܫܡ ܓܘ ܠܘܚܐ ܕܟܢܘܫܝܐ ܒܣ ܡܐ ܕܟܥܒܪ ܠܗ.

▲ ▼ – ܐܝܢܐ ܩܠܝܬܐ ܟܥܒܕܐ ܦܘܪܫܢܐ؟

ܒܘܚܪܢܐ ܪܫܝܡܐ ܟܐܡܪ ܕܐܝܬ ܐܣܘܪܐ، ܠܐ ܐܝܟܐ. ܩܐ ܟܠ ܩܠܝܬܐ ܐܗܐ ܦܐܬܐ ܟܚܫܒ ܫܪܟܐ ܡܬܩܢܐ-ܡܬܘܪܨܐ (Adjusted Residual ܕ-SPSS): ܦܘܪܫܢܐ ܒܝܢܝ ܚܙܝܐ ܘܡܣܟܝܐ، ܡܬܩܢܐ ܐܦ ܠܪܒܘܬܐ ܕܣܕܪܐ ܘܕܥܡܘܕܐ، ܗܕܟܐ ܕܐܝܢܐ ܦܠܝܓܐ ܝܠܗ ܒܩܘܪܒܐ ܐܝܟ z. ܩܠܝܬܐ ܠܥܠ ܡܢ 1.96 – ܝܬܝܪ ܡܢ ܡܣܟܝܐ ܓܘ ܠܐ ܬܠܝܘܬܐ (▲)؛ ܠܬܚܬ ܡܢ −1.96 – ܒܨܝܪ (▼) (Field, 2024، ܦܣܩܐ 19.8 – ܫܪܟܐ ܡܬܩܢܐ ܡܢܝܢܐ z ܝܠܗ، ܘܬܚܘܡܐ ±1.96؛ Pallant, 2020، ܨܚܚܐ 16 – ܬܚܘܡܐ 2 ܩܐ ܫܪܟܐ ܡܬܘܪܨܐ، "ܐܝܟ ܒܘܚܪܢܐ ܕܒܬܪ ܗܕܐ (post hoc)"). ܪ̈ܘܫܡܐ ܟܡܬܚܙܝ ܒܣ ܐܡܬܝ ܕܐܝܬ ܒܘܚܪܢܐ، ܘܐܦ ܐܡܬܝ ܕܠܐ ܝܠܗ ܪܫܝܡܐ – ܘܗܝܓܝ ܐܢܝ ܟܡܚܘܝ ܩܠܝܬܐ ܕܟܦܪܫܐ ܓܘ ܠܘܚܐ ܕܒܟܠܗ ܠܐ ܝܠܗ ܦܪܝܫܐ ܡܢ ܡܣܟܝܐ؛ ܟܩܪܚ ܠܗܘܢ ܐܝܟ ܐܘܪܚܐ، ܠܐ ܐܝܟ ܡܫܟܚܢܘܬܐ ܒܓܢܗ. ܫܪ̈ܟܐ ܒܓܢܗܘܢ، ܡܣܟܝܐ ܩܐ ܟܠ ܩܠܝܬܐ ܘܫܪܟܐ ܕܦܘܪܫܐ ܟܩܒܠܚ ܩܐ ܠܘܚܐ ܝܚܝܕܝܐ ܓܘ ܟܝ ܡܪܒܥܐ.

ܦܘܢ̈ܝܐ ܣܓܝ̈ܐܐ، ܣܕܪ̈ܐ ܕܫܘܐ̈ܠܐ ܘܡܫܬܚܠܦ̈ܢܐ ܡܬܡܫܚ̈ܢܐ ܠܦܘܬ ܓܘܕܐ

ܦܘܢ̈ܝܐ ܣܓܝ̈ܐܐ (multiple response). ܣܕܪܐ ܩܐ ܟܠ ܓܘܒܝܐ، ܩܠܝܬܐ = ܡܢܬܐ ܒܡܐܐ ܕܡܦܢܝ̈ܢܐ ܓܘ ܥܡܘܕܐ ܕܪܫܡܠܗܘܢ ܠܗ (Percent of Cases ܓܘ MULT RESPONSE)؛ ܓܘܡܪܐ ܕܥܡܘܕܐ ܟܥܒܪ ܥܠ 100. ܣܕܪܐ ܕܫܬܐܣܐ – ܡܦܢܝ̈ܢܐ ܕܦܢܠܗܘܢ (ܪܫܡܠܗܘܢ ܚܕ ܓܘܒܝܐ ܠܟܡܝܘܬܐ) ܓܘ ܟܠ ܓܘܕܐ، ܒܝܢܝ ܫܘ̈ܝܐ. ܠܝܬ ܚܕ ܒܘܚܪܢܐ ܩܐ ܠܘܚܐ ܐܝܟ ܐܗܐ؛ ܟܠ ܓܘܒܝܐ ܡܫܬܚܠܦܢܐ 0/1 ܝܠܗ، ܘܐܝܢܐ ܕܒܥܐ ܒܘܚܪܢܐ ܟܪܗܛ ܟܝ ܡܪܒܥܐ ܩܐ ܓܘܒܝܐ × ܓܘܕܐ ܓܘ ܦܐܬܐ ܕܟܝ ܡܪܒܥܐ.

ܣܕܪ̈ܐ ܕܫܘܐ̈ܠܐ (batteries). ܣܕܪܐ ܩܐ ܟܠ ܦܣܘܩܐ، ܩܠܝܬܐ = ܡܨܥܝܬܐ ܕܪ̈ܡܙܐ (ܡܬܠܐ 1-5) ܓܘ ܓܘܕܐ ܘ-N ܕܦܣܘܩܐ ܓܘ ܩܘܠܦ̈ܐ – "ܠܐ ܝܕܥܢ" ܠܒܪ ܡܢ ܡܨܥܝܬܐ، ܐܝܟ ܓܘ ܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ. ܥܝܕܐ ܕܣܐܝܛ (site convention): ܩܐ ܣܒܠܬܐ ܕ-Likert ܡܨܥܝܬܐ ܡܚܘܝܢܐ ܕܟܢܘܫܝܐ ܝܠܗ ܒܣ؛ ܦܘܪܫܢܐ ܒܝܢܝ ܓܘ̈ܕܐ ܒܚܝܪܐ ܝܠܗ ܓܘ ܦܘܫܩܐ ܕܫܘܚܠܦܐ (ܝܢ Kruskal-Wallis)، ܘܩܐ ܬܪܬܝܢ ܓܘ̈ܕܐ ܓܘ ܒܘܚܪܢܐ t.

ܡܬܡܫܚ̈ܢܐ. ܡܨܥܝܬܐ، ܣܛܝܘܬܐ ܬܩܝܢܬܐ (ܒܡܦܠܓܢܐ n − 1)، ܛܝܡܐ ܡܨܥܝܐ، ܛܝܡܐ ܬܚܬܝܐ-ܥܠܝܐ ܘ-N ܩܐ ܟܠ ܓܘܕܐ – ܠܘܚܐ ܕ"ܬܚܘܝܬܐ ܠܦܘܬ ܓܘܕܐ" ܕܨܚܚܐ ܕܐܘܪܚܐ (method section). ܐܦ ܠܐܟܐ ܒܘܚܪܢܐ ܓܘ ܦܐ̈ܬܐ ܕܣܛܐܛܝܣܛܝܩܐ ܕܫܘܠܡܐ.

ܡܬܩܠܢܘܬܐ ܓܘ ܦܘܠ̈ܓܐ ܕܥܡܘ̈ܕܐ

ܐܡܬܝ ܕܦܐܝܠ ܡܬܩܠܐ ܝܠܗ ܓܘ ܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ (ܡܢܘ̈ܬܐ ܕܩܠ̈ܝܬܐ ܟܡܬܛܥܢܝ ܡܢ ܓܢܗܘܢ)، ܡܢܘ̈ܬܐ ܒܡܐܐ ܓܘ ܟܠ ܥܡܘܕܐ ܡܬܩ̈ܠܐ ܝܢܐ ܘܣܕܪܐ ܕ"ܫܬܐܣܐ ܡܬܩܠܐ" ܟܡܬܘܣܦܐ ܥܠ ܣܕܪܐ ܕ-n. ܢܡܘܣܐ ܕܐܘܪܚܐ ܕܥܒܕܐ ܐܦ ܠܐܟܐ ܝܠܗ: ܟܡܚܘܚ n ܫܪܝܪܐ ܕܠܐ ܡܬܩܠܐ، ܘܫܬܐܣܐ ܡܬܩܠܐ ܓܢܒܗ – "ܠܐ ܡܨܝܚ ܕܩܪܝܚ ܠܓܘܡܪܐ ܕܡܬ̈ܩܠܐ ܡܢܝܢܐ ܕܡܦܢܝ̈ܢܐ".

ܒܘܚܪܢܐ ܥܠ ܡܢܝ̈ܢܐ ܫܪ̈ܝܪܐ. ܟܝ ܡܪܒܥܐ ܟܣܒܪ ܕܟܠ ܚܙܝܬܐ (observation) ܚܕ ܡܦܢܝܢܐ ܝܠܗ؛ ܪܗܛܐ ܕܝܠܗ ܥܠ ܡܢܝ̈ܢܐ ܡܬܩ̈ܠܐ (ܐܝܟ ܕ-SPSS ܟܥܒܕ ܒܬܪ WEIGHT BY) ܟܚܫܒ ܡܬܩܠܐ 1.7 ܐܝܟ ܕܐܝܬ ܗܘܘ 1.7 ܐܢܫ̈ܐ، ܘܓܘ ܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܕܓܘܗ ܡܬ̈ܩܠܐ ܟܡܪܒܝ ܓܘܕܐ ܙܥܘܪܬܐ – ܟܡܪܒܐ ܪܫܝܡܘܬܐ. ܡܛܠ ܗܕܐ ܐܗܐ ܦܐܬܐ ܟܚܫܒ χ²، V ܘܫܪ̈ܟܐ ܥܠ ܡܢܝ̈ܢܐ ܕܠܐ ܡܬܩܠܢܘܬܐ، ܘܟܡܚܘܐ ܐܗܐ ܓܘ ܟܠ ܡܥܝܪܢܘܬܐ؛ ܣܝܢܬܐܟܣ ܕܟܡܚܬ ܟܒܢܐ ܡܢܘ̈ܬܐ ܒܡܐܐ ܡܬܩ̈ܠܬܐ ܘܒܘܚܪ̈ܢܐ ܓܘ ܬܪܝܢ ܓܘ̈ܫܡܐ (blocks؛ WEIGHT BY / WEIGHT OFF). ܒܘܚܪܢܐ ܕܟܚܫܒ ܡܬ̈ܩܠܐ ܒܬܪܝܨܘܬܐ (Rao-Scott، ܬܘܪܨܐ ܕ-design effect) ܠܐ ܝܠܗ ܓܘ ܐܗܐ ܦܐܬܐ – ܚܙܝܡܘܢ ܡܘܕܝ ܠܐ ܟܥܒܕ ܐܗܐ ܦܐܬܐ.

ܬܘܢܝܐ

ܠܘ̈ܚܐ ܒܢܝ̈ܐ ܝܢܐ ܠܦܘܬ APA: ܡܢܝܢܐ ܕܠܘܚܐ ܘܪܫܐ ܠܥܠ، ܪܫܐ ܥܠܝܐ ܩܐ ܟܠ ܓܘܕܐ ܕܥܡܘ̈ܕܐ (ܡܫܬܚܠܦܢܐ ܕܬܚܘܝܬܐ) ܘܪ̈ܫܐ ܬܚܝ̈ܬܐ ܩܐ ܓܢ̈ܣܐ، ܥܡܘܕܐ ܕ-stub ܩܐ ܦܘܢ̈ܝܐ، ܣܕܪܐ ܕܓܘܡܪܐ ܘܣܕܪܐ ܕ-n، ܘܡܥܝܪܢܘܬܐ ܟܠܢܝܬܐ ܠܬܚܬ ܕܟܡܦܫܩܐ ܫܬܐܣܐ ܘܒܘܚܪܢܐ (APA, 2020, Sections 7.14 and 7.21). ܓܘ Word ܠܘܚܐ ܟܡܬܬܒܪ ܠܣܕܪ̈ܐ ܐܡܬܝ ܕܦܬܝܐ ܝܠܗ – ܡܘܕܥܢܘܬܐ ܩܐ ܡܫܠܡܢܘܬܐ ܟܓܒܝܐ 2-3 ܪ̈ܫܐ ܕܥܡܘ̈ܕܐ ܩܐ ܠܘܚܐ، ܝܢ ܟܒܢܝܐ ܗܢ ܫܘܐܠܐ ܟܡܐ ܓܗ̈ܐ ܥܡ ܪ̈ܫܐ ܕܥܡܘ̈ܕܐ ܦܪ̈ܝܫܐ. ܡܢܝ̈ܢܐ ܒܬܪܬܝܢ ܡܢܝ̈ܢܐ ܘܕܠܐ ܨܦܪܐ ܩܕܡܝܐ ܩܐ V ܘ-p (APA, 2020, Section 6.36)؛ ܓܘ ܟܬܒܐ – χ²(df, N = n) = x.xx, p = .xxx, V = .xx (ܬܡܢ، ܦܣܩܐ 6.43). ܡܐܡܪ̈ܐ ܕܬܘܢܝܐ ܕܐܗܐ ܦܐܬܐ ܟܟܬܒ (ܣܘܪܝܬ ܘܐܢܓܠܝܙܝܐ) ܟܐܡܪܝ ܠܦܘܬ ܡܘܕܝ ܦܠܝܓܐ ܝܠܗ، ܟܡܐ ܒܘܚܪ̈ܢܐ ܪܗܛ̈ܐ ܝܢܐ، ܐܝܢܝ ܨܠܝܒ̈ܘܬܐ ܪܫܝܡ̈ܐ ܝܢܐ – ܟܠ ܚܕܐ ܥܡ ܡܢܝܢܐ ܣܛܐܛܝܣܛܝܩܝܐ، ܪܒܘܬܐ ܕܡܥܒܕܢܘܬܐ ܘܦܘܪܫܢܐ ܓܠܝܐ ܒܝܢܝ ܬܪܬܝܢ ܓܘ̈ܕܐ – ܘܡܘܕܝ ܠܐ ܡܫܟܚܐ ܝܠܗ. ܓܘ ܨܚܚܐ ܕܡܫܟܚ̈ܢܘܬܐ (results chapter) ܟܡܬܠܠܚ ܠܘܚܐ ("ܠܘܚܐ 4") ܘܡܐܡܪܐ؛ ܩܐ ܢܡܘ̈ܣܐ ܕܬܘܢܝܐ ܘܩܐ ܡܘܠܕܢܐ ܕܨܚܚܐ ܕܡܫܟܚ̈ܢܘܬܐ – ܫܪܟܐ.

ܡܘܕܝ ܠܐ ܟܥܒܕ ܐܗܐ ܦܐܬܐ (ܥܕܟܡܐ ܠܐ)

• ܒܘܚܪܢܐ ܩܐ ܦܘܢ̈ܝܐ ܣܓܝ̈ܐܐ ܠܦܘܬ ܓܘܕܐ – ܠܝܬ ܚܕ ܡܢܝܢܐ ܣܛܐܛܝܣܛܝܩܝܐ ܩܐ ܠܘܚܐ ܐܝܟ ܐܗܐ؛ ܩܐ ܟܠ ܓܘܒܝܐ – ܟܝ ܡܪܒܥܐ ܒܦܪܝܫܘܬܐ.
• ܐܬܘ̈ܬܐ ܕܪܫܝܡܘܬܐ ܒܝܢܝ ܥܡܘ̈ܕܐ (column proportions test – A, B, C ܓܢܒ ܡܢܬܐ ܒܡܐܐ، ܐܝܟ ܓܘ CTABLES؛ Field, 2024، ܦܣܩܐ 19.8) – ܠܐ؛ ܐܝܬ ▲/▼ ܠܦܘܬ ܫܪ̈ܟܐ ܩܘܒܠ ܡܣܟܝܐ، ܠܐ ܦܘܚܡܐ ܙܘܓܢܝܐ ܒܝܢܝ ܟܠ ܬܪܬܝܢ ܥܡܘ̈ܕܐ.
• ܦܘܠܓܐ ܠܦܘܬ ܬܪܝܢ ܡܫܬܚܠܦ̈ܢܐ ܒܚܕ ܙܒܢܐ (ܩܠ̈ܝܬܐ ܙܥܘܪ̈ܐ: ܓܒܪ̈ܐ ܥܠܝܡ̈ܐ، ܓܒܪ̈ܐ ܣܒ̈ܐ…) – ܠܐ؛ ܟܒܢܝܚ ܡܫܬܚܠܦܢܐ ܡܪܟܒܐ ܒܪܡܙܢܘܬܐ ܡܢ ܪܝܫ ܝܢ ܓܘ ܪܡܙܢܘܬܐ ܕܦܘܢ̈ܝܐ، ܘܐܝܢܐ ܟܗܘܐ ܪܫܐ ܕܥܡܘ̈ܕܐ.
• ܒܘܚܪ̈ܢܐ ܡܬܩ̈ܠܐ (Rao-Scott، ܛܥܝ̈ܘܬܐ ܬܩܝ̈ܢܬܐ ܥܡ design effect) ܘܬܚܘ̈ܡܐ ܕܬܘܟܠܢܐ (confidence intervals) ܩܐ ܡܢܘ̈ܬܐ ܒܡܐܐ – ܠܐ؛ ܒܘܚܪܢܐ ܥܠ ܡܢܝ̈ܢܐ ܫܪ̈ܝܪܐ ܝܠܗ.
• ܬܘܪܨܐ ܩܐ ܒܘܚܪ̈ܢܐ ܣܓܝ̈ܐܐ (Bonferroni، FDR) – ܠܐ ܡܢ ܓܢܗ؛ ܠܘܚܐ ܕܟܢܘܫܝܐ ܟܝܗܒ ܟܠ ܛܝ̈ܡܐ ܕ-p، ܘܒܨܘܝܬܐ ܟܦܣܩܐ.
• ܨܘܪ̈ܬܐ ܩܐ ܦܘܠ̈ܓܐ ܕܥܡܘ̈ܕܐ – ܠܐ ܓܘ ܐܗܐ ܢܘܣܚܐ.
• ܚܘܝܕܐ ܕܦܐܝ̈ܠܐ – ܓܘ ܦܐܬܐ ܕܦܘܠܚܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ؛ ܟܚܝܕܚ ܬܡܢ، ܟܡܚܬܚ ܦܐܝܠ، ܘܟܛܥܢܚ ܠܐܟܐ.

ܘܕܟܝ ܟܥܒܕܚ ܐܗܐ ܒ-SPSS؟ (And how do you do it in SPSS?)

Analyze › Descriptive Statistics › Crosstabs: ܫܘܐܠܐ ܓܘ Row(s)، ܡܫܬܚܠܦܢܐ ܕܬܚܘܝܬܐ ܓܘ Column(s)؛ ܓܘ Cells… ܟܪܫܡܚ Column ܓܘ ܡܢܘ̈ܬܐ ܒܡܐܐ ܘ-Adjusted standardized ܓܘ ܫܪ̈ܟܐ؛ ܓܘ Statistics… – Chi-square ܘ-Phi and Cramer's V (Pallant, 2020, Chapter 16; Field, 2024, Chapter 19). ܓܘ ܡܦܩܢܐ: % within [ܬܚܘܝܬܐ] ܝܠܗ ܡܢܬܐ ܒܡܐܐ ܕܥܡܘܕܐ ܓܘ ܐܗܐ ܦܐܬܐ؛ Pearson Chi-Square، df ܘ-Asymptotic Significance – ܣܕܪܐ ܕܒܘܚܪܢܐ؛ Cramer's V – ܓܘ Symmetric Measures. ܣܝܢܬܐܟܣ (syntax) ܕܐܗܐ ܦܐܬܐ ܟܡܚܬ ܟܥܒܕ ܟܠ ܐܗܐ: CROSSTABS /TABLES=ܫܘܐ̈ܠܐ BY ܪ̈ܫܐ-ܕܥܡܘ̈ܕܐ /CELLS=COUNT COLUMN /STATISTICS=CHISQ PHI – ܦܘܩܕܢܐ ܚܕ ܩܐ ܟܠ ܫܘܐ̈ܠܐ ܪ̈ܓܝܠܐ، ܘܝܬܝܪ TEMPORARY + SELECT IF ܩܐ ܫܘܐܠܐ ܬܠܝܐ؛ ܩܕܡܗ ܦܘܩܕ̈ܢܐ ܕܟܬܒܐ ܕܪ̈ܡܙܐ (MISSING VALUES ܩܐ "ܠܐ ܝܕܥܢ" – ܗܕܟܐ ܐܦ ܓܘ ܡܫܬܚܠܦܢܐ ܕܬܚܘܝܬܐ ܐܢܝ ܠܐ ܝܢܐ ܥܡܘܕܐ)، ܪܡܙܢܘܬܐ ܡܢ ܪܝܫ، ܡܨܠܠܢܘܬܐ ܘܡܬܩܠܢܘܬܐ، ܘܒܬܪܗ MULT RESPONSE … /TABLES=$ܓܘܕܐ BY ܬܚܘܝܬܐ /CELLS=COLUMN ܩܐ ܦܘܢ̈ܝܐ ܣܓܝ̈ܐܐ ܘ-MEANS ܩܐ ܣܕܪ̈ܐ ܕܫܘܐ̈ܠܐ ܘܩܐ ܡܬܡܫܚ̈ܢܐ.

ܬܠܬܐ ܦܘܪ̈ܫܢܐ ܩܐ ܝܕܥܬܐ: (1) ܥܡܘܕܐ ܕ-Total ܓܘ CROSSTABS ܟܚܒܫ ܒܣ ܡܦܢܝ̈ܢܐ ܥܡ ܛܝܡܐ ܓܘ ܬܪܘܝܗܝ ܡܫܬܚܠܦ̈ܢܐ، ܐܝܢܐ ܥܡܘܕܐ ܕܓܘܡܪܐ ܓܘ ܐܗܐ ܦܐܬܐ ܟܠ ܡܦܢܝ̈ܢܐ ܝܢܐ ܠܫܘܐܠܐ – ܐܡܬܝ ܕܐܝܬ ܣܦܝܩ̈ܐ ܓܘ ܡܫܬܚܠܦܢܐ ܕܬܚܘܝܬܐ ܓܘܡܪܐ ܕ-SPSS ܙܥܘܪܐ ܝܬܝܪ ܝܠܗ. (2) ܛܝܡܐ ܕܠܐ ܝܠܗ ܓܘ ܟܬܒܐ ܕܪ̈ܡܙܐ ܥܡܘܕܐ ܝܠܗ ܓܘ SPSS؛ ܐܡܬܝ ܕܓܘܒܝܐ ܛܦܝܐ ܝܠܗ ܓܘ ܐܗܐ ܦܐܬܐ، ܣܝܢܬܐܟܣ ܟܦܪܫ ܠܗ ܐܝܟ SYSMIS ܓܘ RECODE. (3) ܒܬܪ WEIGHT BY ܐܦ ܒܘܚܪܢܐ ܕ-SPSS ܡܬܩܠܐ ܝܠܗ – ܣܝܢܬܐܟܣ ܟܪܗܛ ܒܘܚܪ̈ܢܐ ܒܬܪ WEIGHT OFF، ܐܝܟ ܓܘ ܐܗܐ ܦܐܬܐ. ܘܣܩܪ̈ܝܦܬܐ ܥܬܝܩ̈ܐ؟ TABLES … BY kk ܥܡ cpct ܒܢܝܠܗܘܢ ܐܗܐ ܠܘܚܐ ܕܠܐ ܒܘܚܪܢܐ؛ TABLES ܠܝܬ ܠܗ ܝܬܝܪ، ܘ-CROSSTABS (ܝܢ CTABLES) ܝܠܗ ܚܠܦܗ.

ܘܕܟܝ ܟܥܒܕܚ ܐܗܐ ܒ-R؟ (And how do you do it in R?)

ܕܠܐ ܚܙܡ̈ܐ ܡܝܚ̈ܕܐ: xtabs(w ~ x + g) ܩܐ ܡܢܝ̈ܢܐ (ܡܬܩ̈ܠܐ ܐܡܬܝ ܕܐܝܬ ܡܬܩܠܐ)، prop.table(tab, 2) ܩܐ ܡܢܘ̈ܬܐ ܒܡܐܐ ܕܥܡܘܕܐ، chisq.test(tab, correct = FALSE) – ܕܠܐ ܬܘܪܨܐ ܕ-Yates، ܐܝܟ ܓܘܒܝܐ ܡܩܕܡܐ ܕ-SPSS ܩܐ Pearson – ܘ-$stdres ܩܐ ܫܪ̈ܟܐ ܡܬܘܪ̈ܨܐ؛ V ܕ-Cramér ܚܫܝܒܐ ܝܠܗ ܒܐܝܕܐ ܡܢ ܡܢܝܢܐ ܣܛܐܛܝܣܛܝܩܝܐ. ܣܩܪܝܦܬ (script) ܕܐܗܐ ܦܐܬܐ ܟܡܚܬ ("ܡܚܬܬܐ ܕܣܩܪܝܦܬ R") ܟܩܪܐ ܦܐܝܠ ܥܡ readxl، ܟܡܦܠܚ ܪܡܙܢܘܬܐ، ܡܨܠܠܢܘܬܐ ܘܡܬܩܠܢܘܬܐ، ܟܦܪܫ ܦܘܢܩܣܝܐ xt() ܕܟܡܦܩܐ NA، ܪ̈ܡܙܐ ܕ"ܠܐ ܝܕܥܢ" ܘܛܝ̈ܡܐ ܕܠܐ ܝܢܐ ܓܘ ܟܬܒܐ ܕܪ̈ܡܙܐ، ܘܟܛܒܥ ܩܐ ܟܠ ܫܘܐܠܐ × ܪܫܐ ܕܥܡܘ̈ܕܐ ܡܢܘ̈ܬܐ ܒܡܐܐ ܕܥܡܘܕܐ، n، ܒܘܚܪܢܐ ܘܫܪ̈ܟܐ – ܘܝܬܝܪ ܣܕܪܐ ܩܐ ܟܠ ܦܘܢ̈ܝܐ ܣܓܝ̈ܐܐ، ܣܕܪܐ ܕܫܘܐ̈ܠܐ ܘܡܬܡܫܚܢܐ. ܢܡܘܣܐ ܕܣܐܝܛ (site rule) ܩܐ ܣܘܪܝܬ ܒ-R: ܦܐܝܠ UTF-8 ܘܐܬܪܐ (locale) UTF-8 (readxl ܠܐ ܒܕ ܡܫܟܚ ܓܠܝܘܢܐ ܒܫܡܐ ܥܒܪܝܐ ܓܘ locale "C")، ܟܠ ܣܕܪܐ ܕܡܥܝܪܢܘܬܐ ܟܫܪܐ ܒܡܠܬܐ ܕܣܘܪܝܬ. ܣܩܪܝܦܬ ܪܗܛܐ ܝܠܗ ܓܘ R 4.3 ܥܠ ܦܐܝܠ ܕܡܬܠܐ ܡܬܩܠܐ ܘܝܗܒܠܗ ܡܢܝ̈ܢܐ ܕܐܗܐ ܦܐܬܐ (README ܕܫܘܪܪܐ).

ܛܥܝ̈ܘܬܐ ܕܡܬܚܙܝܢ ܣܓܝ (Common mistakes)

ܩܪܝܢܐ ܕܡܢܘ̈ܬܐ ܒܡܐܐ ܕܣܕܪܐ ܐܝܟ ܡܢܘ̈ܬܐ ܒܡܐܐ ܕܥܡܘܕܐ. "60% ܡܢ ܒܣܝܡ̈ܐ ܢܫ̈ܐ ܝܢܐ" ܠܐ ܝܠܗ "60% ܡܢ ܢܫ̈ܐ ܒܣܝܡ̈ܐ ܝܢܐ". ܠܘܚܐ ܠܐܟܐ ܡܢܘ̈ܬܐ ܒܡܐܐ ܕܥܡܘܕܐ ܝܢܐ – ܡܢ ܓܘܕܐ، ܟܡܐ ܦܢܠܗܘܢ ܗܕܟܐ – ܘܐܗܐ ܝܠܗ ܦܘܚܡܐ ܬܪܝܨܐ ܒܝܢܝ ܓܘ̈ܕܐ ܒܪ̈ܒܘܬܐ ܦܪ̈ܝܫܐ.

ܡܬܪܓܫܢܘܬܐ ܡܢ ܦܘܪܫܢܐ ܓܘ ܥܡܘܕܐ ܕ-15 ܐܢܫ̈ܐ. 40% ܩܘܒܠ 27% ܡܨܝ ܕܗܘܝ 6 ܩܘܒܠ 4 ܡܦܢܝ̈ܢܐ. ܠܘܚܐ 1 ܘܣܕܪܐ ܕ-n ܩܐ ܐܗܐ ܝܢܐ؛ ܟܚܝܕܚ ܓܢ̈ܣܐ ܝܢ ܟܡܬܢܚ ܡܢܝ̈ܢܐ.

ܡܢܝܢܐ ܕܪ̈ܫܝܡܘܬܐ ܕܠܐ ܡܢܝܢܐ ܕܒܘܚܪ̈ܢܐ. 3 ܨܠܝܒ̈ܘܬܐ ܪܫܝܡ̈ܐ ܡܢ 60 ܒܩܘܪܒܐ ܡܐ ܕܡܣܟܝܐ ܝܠܗ ܒܓܕܫܐ ܝܢܐ. ܟܡܬܢܚ "ܡܢ 60"، ܘܟܦܫܩܚ ܛܘܦܣܐ.

ܫܒܩܬܐ ܕܫܪܛܐ. p ܙܥܘܪܐ ܓܘ ܠܘܚܐ ܕܣܓܝ ܡܢ ܩܠ̈ܝܬܐ ܡܣܟ̈ܝܬܐ ܠܬܚܬ ܡܢ 5 ܝܢܐ ܠܐ ܫܘܐ ܣܓܝ؛ ܠܘܚܐ ܟܪܫܡ "ܫܪܛܐ" – ܟܚܝܕܚ ܘܟܪܗܛܚ ܬܘܒ.

ܪܫܝܡܐ = ܪܒܐ. ܓܘ 1,000 ܡܦܢܝ̈ܢܐ V = .06 ܟܗܘܐ ܪܫܝܡܐ؛ ܐܗܐ ܐܣܘܪܐ ܙܥܘܪܐ ܛܒܐ ܝܠܗ. V ܩܕܡ p.

ܦܘܫܩܐ ܕܦܘܠܓܐ ܐܝܟ ܥܠܬܐ. "ܣܒ̈ܐ ܒܨܝܪ ܒܣܝܡ̈ܐ ܝܢܐ ܡܢ ܬܫܡܫ̈ܬܐ ܕܝܓܝܛܠܝ̈ܬܐ" – ܝܢ ܐܢܝ ܒܨܝܪ ܟܡܦܠܚܝ ܒܝܗܝ. ܠܘܚܐ ܕܬܚܘܝܬܐ × ܬܚܘܝܬܐ ܘ-ܪܝܓܪܫܢ ܠܘܓܝܣܛܝܩܝܐ ܟܒܚܪܝ ܡܢܘ ܟܡܦܫܩ ܠܡܢܘ.

ܛܥܝܘܬܐ ܕܡܢܘ ܠܐ ܝܠܗ ܓܘ ܥܡܘ̈ܕܐ. 20 "ܠܐ ܨܒ̈ܝܢ ܠܡܦܢܝܐ" ܓܘ ܫܘܐܠܐ ܕܐܓܪܐ ܠܐ ܝܢܐ ܓܘ ܚܕ ܥܡܘܕܐ ܕܐܓܪܐ ܐܝܢܐ ܐܝܢ ܓܘ ܓܘܡܪܐ – ܘܐܢ ܐܢܝ ܦܪ̈ܝܫܐ ܝܢܐ، ܓܘܡܪܐ ܠܐ ܝܠܗ ܡܨܥܝܬܐ ܕܥܡܘ̈ܕܐ. ܡܥܝܪܢܘܬܐ ܕܠܘܚܐ ܟܐܡܪܐ ܟܡܐ ܝܢܐ.

ܡܒܘ̈ܥܐ

American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000

Field, A. (2024). Discovering statistics using IBM SPSS statistics (6th ed.). Sage.

Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioral sciences (10th ed.). Cengage Learning.

Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). Routledge.

ܠܦܘܬ ܢܡܘܣܐ ܕܣܐܝܛ (site rule)، ܓܘ ܪܫܝܡܬܐ ܕܡܒܘ̈ܥܐ ܟܡܬܚܙܝ ܒܣ ܡܒܘ̈ܥܐ ܕܩܪܝ̈ܐ ܝܢܐ ܓܘ ܢܘܣܚܐ ܫܪܫܝܐ، ܘܓܘ ܦܣ̈ܩܐ ܕܡܢ ܩܕܡ ܒܚܝܪ̈ܐ ܝܢܐ ܓܘ ܦܐܬܐ ܕܟܝ ܡܪܒܥܐ: Field – ܨܚܚܐ 19 (ܦܣ̈ܩܐ 19.3, 19.5.2, 19.5.3, 19.8)، Pallant – ܨܚ̈ܚܐ 8 ܘ-16، Gravetter ܘ-Wallnau – ܦܣܩܐ 17.4، ܫܘܝܘܬܐ 17.9 ܘܠܘܚܐ 17.10، APA – ܦܣ̈ܩܐ 6.36, 6.43, 7.14 ܘ-7.21. Cohen (1988) ܡܬܡܠܠ ܝܠܗ ܐܝܟ ܕܡܬܡܠܠ ܓܘ Pallant ܘܓܘ Gravetter ܘ-Wallnau. ܐܘܪܚܐ ܕܥܒܕܐ ܘܣܩܪ̈ܝܦܬܐ ܕ-TABLES ܟܬܒ̈ܐ ܕܥܒܕܐ ܕܣܐܝܛ ܝܢܐ ܘܠܐ ܝܢܐ ܡܒܘ̈ܥܐ ܡܦܪ̈ܣܐ. ܚܘܫܒܢܐ ܓܘ ܐܗܐ ܦܐܬܐ ܒܚܝܪܐ ܝܠܗ ܩܘܒܠ Python (pandas, scipy) ܥܠ ܦܐܝܠ ܕܡܬܠܐ – ܟܠ ܡܢܬܐ ܒܡܐܐ، ܟܠ ܫܬܐܣܐ، ܟܠ χ², p, V ܘܪܘܫܡܐ ܕܫܪܟܐ، ܓܘ ܬܠܬܐ ܫܬܐܣ̈ܐ، ܕܠܐ ܡܢܝ̈ܢܐ ܒܬܪ ܢܘܩܙܐ، ܥܡ ܘܕܠܐ ܥܡܘ̈ܕܐ ܩܐ ܛܝ̈ܡܐ ܕܠܐ ܝܢܐ ܓܘ ܟܬܒܐ ܕܪ̈ܡܙܐ، ܓܘ ܦܘܢ̈ܝܐ ܣܓܝ̈ܐܐ، ܓܘ ܣܕܪܐ ܕܫܘܐ̈ܠܐ، ܓܘ ܡܬܡܫܚܢܐ ܘܓܘ ܣܩܪܝܦܬ ܡܬܩܠܐ (ܪܡܙܢܘܬܐ، ܡܨܠܠܢܘܬܐ، ܡܬܩܠܢܘܬܐ) – ܘܩܘܒܠ PSPP (CROSSTABS) ܘ-R (chisq.test, prop.table, stdres)؛ ܚܙܝܡܘܢ README ܕܫܘܪܪܐ.