Conducting a Simple Linear Regression in SPSS with Assumption Testing

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  • Опубликовано: 4 окт 2024
  • This video demonstrates how to conduct and interpret a simple linear regression in SPSS including testing for assumptions. A simple linear regression determines the percentage of variance in a dependent variable that is attributable to a single independent variable.

Комментарии • 39

  • @humoaz6629
    @humoaz6629 2 года назад +1

    Thanks so much Dr Grande. I learn so much from you videos that I can't even begin to tell. Your explanation is great, voice is clear and the flow is just the perfect. Bless you for contributing to education.

  • @ginnamyers3059
    @ginnamyers3059 8 лет назад +2

    Your videos are exceptional! They are more, more, more helpful than my textbook! Thank you!!!!

  • @elsi8224
    @elsi8224 4 года назад +7

    what if the dependent variables not normally distributed, can i still run the next assumptions?

  • @JamieB
    @JamieB 5 лет назад

    I like that you took your time to explain step by step. It would be easy to follow along and practice linear regressions while watching your video!

  • @vanessagraham6473
    @vanessagraham6473 8 лет назад

    This really helps to break down the steps involved and understand the importance of each.

  • @TuMaLife
    @TuMaLife 4 года назад +2

    Really good video. I like how you explained everything that is important to a Regression. Thank you

    • @TuMaLife
      @TuMaLife 4 года назад

      How should we sort our data for example, I want to study data for a country for a 5 year period. How should I input those 5 years data in SPSS?

  • @keithwilkerson9074
    @keithwilkerson9074 8 лет назад

    Excellent demonstration of the logic and operations required to conduct a simple linear regression in SPSS.

  • @saraspong6698
    @saraspong6698 8 лет назад

    Wish I would have found this one before I took the exam! Never the less very helpful for our upcoming assignment!

  • @joelcagwin3593
    @joelcagwin3593 8 лет назад

    Thanks for a clear explanation for running a simple linear regression

  • @zalaarbab8537
    @zalaarbab8537 7 лет назад

    This video is the only video i understood...Thank You!

    • @DrGrande
      @DrGrande  7 лет назад

      You're welcome - thank you for watching.

  • @bradleyfairchild1208
    @bradleyfairchild1208 8 лет назад

    Helpful for studying for the exam, thanks.

  • @coolguy32558
    @coolguy32558 3 года назад

    This video was so helpful!

  • @ahmadaadaqqa
    @ahmadaadaqqa 2 года назад

    Thank you for your amazing demonstration
    but what if we have to conduct a linear relationship test on not-normally distributed variables?

  • @tskirchner.phd.lmft.20
    @tskirchner.phd.lmft.20 8 лет назад +1

    You mentioned the assumption of not having outliers but didn't cover how this is checked. Are you using Cook's D or the Std. Residual numbers to assess for outliers? Also, you looked at the R squared value to assess the significance of prediction. I thought that the p value in the Sig. column of the ANOVA table would tell us the significance of prediction. Is this incorrect?

  • @barirahkhan6179
    @barirahkhan6179 7 лет назад +1

    Can regression and/or correlation be done when one has a large number of DEPENDENT VARIABLES and one Independent Variable (treatment groups) in an experimental study?

  • @sannyuharris2827
    @sannyuharris2827 8 лет назад

    Thank you for the video!

  • @musicislife686
    @musicislife686 6 лет назад +1

    Why does the St. Residual and the Stud. Residual have to be between -3 and +3 under the "Residual Statistics" Table?

    • @dawn123ish
      @dawn123ish 5 лет назад

      Standard deviations. Values further out indicate the presence of outliers that will skew the data. This is important because 99% of the values should fall within 3 st. deviations. So, to have data that fall outside of 3, means there is a problem with the linear regression model.

  • @nayabfarhat5198
    @nayabfarhat5198 4 года назад +2

    why you want correlation between two variable greater than .3?

    • @WildHeartAngel3
      @WildHeartAngel3 3 года назад

      Were you able to figure this out? I'm trying to find out myself why this is.

    • @nayabfarhat5198
      @nayabfarhat5198 3 года назад

      @@WildHeartAngel3 Values between 0.3 and 0.7 (-0.3 and -0.7) indicate a moderate positive (negative) linear relationship via a fuzzy-firm linear rule. Values between 0.7 and 1.0 (-0.7 and -1.0) indicate a strong positive (negative) linear relationship via a firm linear rule.

  • @somesimple
    @somesimple 8 лет назад

    I have been following your videos on SPSS and they have helped me alot. Can I discuss with you Regression if you could spare some time for that. Thank you.

  • @nicolewalton6155
    @nicolewalton6155 8 лет назад

    Helpful - thank you!

  • @corieschoeneberg9295
    @corieschoeneberg9295 8 лет назад

    Very helpful video

  • @TuMaLife
    @TuMaLife 4 года назад

    How should we sort our data in Excel, for example, I want to study data for a country for a 5 year period. How should I input those 5 years data in SPSS? Should I upload each year separately into SPSS from Excel?

  • @bethmackenzie2358
    @bethmackenzie2358 Год назад

    What do you do if your unstandardised B constant is a negative number?

  • @trishaudumudi
    @trishaudumudi 2 года назад

    Thank you for thiss!

  • @SaraS-uk3dm
    @SaraS-uk3dm 4 года назад

    How do we report the assumption testing in writing in our essays

  • @SaraS-uk3dm
    @SaraS-uk3dm 4 года назад

    For normality testing if I put four variables and two of these came back non statistically significant and the other two didn’t. What does this suggest about my hypothesis

    • @antonmand3671
      @antonmand3671 8 месяцев назад

      This probably suggests that two of your variables are not normally distributed, which means you have to run a non-parametric alternative to the pearson correlation using Kendalls tau or spearman's rho, if you get a significant result for the correlation, try to run the regression anyways, as long as the other assumptions are met, the violation of normality should not play a very big role.

  • @andyk5802
    @andyk5802 3 года назад

    You show to conduct assumption testing, but you do not explain what the output is for (i.e., what does the standardized residual needing to fall between -3 and 3 indicate? outliers?)

  • @timstauffer1351
    @timstauffer1351 8 лет назад

    Thank you

  • @terihourihan6896
    @terihourihan6896 8 лет назад

    thank you.

  • @fassikawkebede4359
    @fassikawkebede4359 3 года назад

    very interesting

  • @chrisvanderwende961
    @chrisvanderwende961 6 месяцев назад

    vo